Expert system for well treatment

ABSTRACT

A method of controlling a pumping sequence of a fracturing fleet at a wellsite while performing a fracturing job on a treatment wellbore penetrating a subterranean formation. A modeling application receives sensor data from the treatment wellbore and/or a monitoring wellbore, predicts a fracture propagation within the formation, and produces a pumping sequence to obtain the fracture propagation or a real-time update to the pumping sequence. The pumping can include two or more sub-stages, wherein the modeling application employs a first pumping routine model to provide a first sub-stage of the pumping sequence and employs a second pumping routine model to provide a second sub-stage of the pumping sequence. A managing application controls the fracturing fleet in accordance with the pumping sequence to place a fracturing fluid in the treatment well.

CROSS-REFERENCE TO RELATED APPLICATIONS

None.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

REFERENCE TO A MICROFICHE APPENDIX

Not applicable.

BACKGROUND

Subterranean hydraulic fracturing is conducted to increase or“stimulate” production from a hydrocarbon well. To conduct a fracturingprocess, high pressure is used to pump special fracturing fluids,including some that contain propping agents (“proppants”) down-hole andinto a hydrocarbon formation to split or “fracture” the rock formationalong veins or planes extending from the well-bore. Once the desiredfracture is formed, the fluid flow is reversed and the liquid portion ofthe fracturing fluid is removed. The proppants are intentionally leftbehind to stop the fracture from closing onto itself due to the weightand stresses within the formation. The proppants thus literally“prop-apart”, or support the fracture to stay open, yet remain highlypermeable to hydrocarbon fluid flow since they form a packed bed ofparticles with interstitial void space connectivity. Sand is one exampleof a commonly-used proppant. The newly-created-and-propped fracture orfractures can thus serve as new formation drainage area and new flowconduits from the formation to the well, providing for an increasedfluid flow rate, and hence increased production, of hydrocarbons.

To plan a fracturing fluid pumping process to create a targeted fractureprofile in a subterranean formation penetrated by a wellbore, fracturingmodels can be used which predict the propagation of fractures through aformation of given mechanical properties in relation the pumped volume,pumping rate, and rheologic properties of the fracturing fluid beingused. The pumping process can be automated with a pumping sequenceutilizing the fracturing model to develop a pumping sequence with thepump rates, fluid volume, and slurry density.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure, referenceis now made to the following brief description, taken in connection withthe accompanying drawings and detailed description, wherein likereference numerals represent like parts.

FIG. 1 is a schematic diagram of a wellbore penetrating a subterraneanformation and associated equipment for recovering resources from thewellbore.

FIG. 2A is a block diagram of a hydraulic fracturing system according toan embodiment of the disclosure.

FIG. 2B is a block diagram of an instrumented package for a hydraulicfracturing system according to an embodiment of the disclosure.

FIG. 3 is a block diagram of a water supply unit for a hydraulicfracturing system according to an embodiment of the disclosure.

FIG. 4 is a block diagram of a hierarchy of an expert system forfracturing modeling and associated wellbore fracturing operationsaccording to an embodiment of the disclosure.

FIG. 5 is a schematic diagram of a communication system according to anembodiment of the disclosure.

FIGS. 6A and 6B are illustrations of a pumping sequence according to anembodiment of the disclosure.

FIG. 7 is a logical flow diagram depicting a plurality of sub-stagescripts associated with a pumping sequence for a fracturing stageaccording to an embodiment of the disclosure.

FIG. 8 is a logical flow diagram depicting a method for preparing anautomated pumping sequence of the type represented by FIG. 7.

FIG. 9 is a logical flow diagram depicting an operational method ofcarrying out an automated pumping sequence according to an embodiment ofthe disclosure.

FIG. 10 is a logical flow diagram depicting an operational method ofupdating an automated pumping sequence via fracture modeling accordingto another embodiment of the disclosure.

FIG. 11 is a logical flow diagram depicting an operational method ofupdating an automated pumping sequence via fracture modeling accordingto another embodiment of the disclosure.

FIG. 12 is a flow chart of method of controlling a pumping sequence of afracturing fleet at a wellsite while performing a fracturing job on atreatment wellbore penetrating a subterranean formation according to anembodiment of the disclosure.

FIG. 13 is a flow chart of still another method of controlling a pumpingsequence of a fracturing fleet at a wellsite while performing afracturing job on a treatment wellbore penetrating a subterraneanformation according to an embodiment of the disclosure.

FIG. 14A is a block diagram of an exemplary communication systemaccording to an embodiment of the disclosure.

FIG. 14B is a block diagram of a 5G core network according to anembodiment of the disclosure.

FIG. 15 is a block diagram of a computer system according to anembodiment of the disclosure.

DETAILED DESCRIPTION

It should be understood at the outset that although illustrativeimplementations of one or more embodiments are illustrated below, thedisclosed systems and methods may be implemented using any number oftechniques, whether currently known or not yet in existence. Thedisclosure should in no way be limited to the illustrativeimplementations, drawings, and techniques illustrated below, but may bemodified within the scope of the appended claims along with their fullscope of equivalents.

A modern fracturing fleet typically includes a water supply, a proppantsupply, one or more blenders, a plurality of frac pumps, and afracturing manifold connected to the wellhead. The individual units ofthe fracturing fleet can be connected to a central control unit called adata van. The control unit can control the individual units of thefracturing fleet to provide proppant slurry at a desired rate to thewellhead. The control unit can manage the pump speeds, chemical intake,and proppant density while pumping fracturing fluids and receiving datarelating to the pumping from the individual units.

Service personnel have typically directed the pumping of fracturingfluids from the control unit to follow the pumping sequence of afracturing model. This direction provided by the service personnel canbe manual direction, changes to an automated schedule, or both. Forexample, the service personnel may monitor an automated pumping sequenceduring a pumping stage then switch to manual control due to an unplannedevent, change the pump rate, or some other pumping process. Thesechanges, also called exceptions, to the automated pumping sequence canbe due to a change in the pumping equipment (e.g., line leak), a changein the wellbore environment (e.g., sand out, also referred to a sandscreen out or simply a screen out), a requested change from thecustomer, or other considerations. These exceptions may not bepredictable but the remedial changes required to the pumping sequencecan be predictable and/or selected from a predetermined list ofavailable remedial actions.

Exceptions to an automated pumping sequence can create costly delaysand, in some cases, a safety hazard. For example, a frac pump maydevelop a leak around the plunger seals causing a loss of pumpingefficiency and a possible environmental cleanup. The frac pump must beisolated and repaired or replaced. The process of isolating a leakingpump during a pumping stage may be difficult for inexperienced servicepersonnel. The lack of experience can cause a delay in the repair, apremature end to the pumping stage, and a possible health, safety, orenvironmental (HSE) hazard.

In an embodiment, a managing application can control a pumping sequencefor a fracturing fleet at a wellsite. The managing application canretrieve a pumping sequence from a storage server. The pumping sequencecan include multiple stages corresponding to a pumping operation such asa pump rate test, a ramp up stage, a single zone fracturing, and cleanup. The pumping sequence can include a single zone or multiple zones tobe fractured. Each pumping stage can be controlled by a stage scriptwritten in a scripting computer language such as Python, Java, Perl,Ruby, Tcl, or Smalltalk. The stage script can be a set of instructionsfor each fracturing unit to follow during a pumping stage. The stagescript may link two or more fracturing units together during a pumpingstage. For example, the stage script instructions can include the sameinstructions to two or more pumps during a pumping stage. The fracturingunit can return data (e.g., pressure, temperature, etc.) to the managingapplication during the pumping stage. The data from the fracturing unitsis compared to the expected equipment output based on the pumpingsequence. When the equipment data doesn't match the predicted equipmentoutput, the managing application can produce an exception notice thatreturns control to the service personnel. The exception notice mayindicate a leak, a pump failure, or an event in the well (e.g.,sandout). The service personnel can take remedial action to correct theexception.

In an embodiment, the automated pumping sequence can have automatedexception handling to clear common exceptions. For example, an automatedpumping script executed by a managing application may include additionalautomated exception/remedial scripts that are triggered when anexception occurs. For example, the automated exception handling may idlea leaking pump and close valves to isolate the pump from the manifold.The automated exception handling may attempt one, two, or more automatedexception/remedial scripts before issuing an exception notice andreturning control to the service personnel.

Disclosed herein are methods of controlling a pumping sequence of afracturing fleet at a wellsite while performing a fracturing job on atreatment wellbore penetrating a subterranean formation. A modelingapplication receives one or more user inputs related to the fracturingjob, one or more equipment inputs comprising sensor data from one ormore frac units of the fracturing fleet, one or more wellbore inputscomprising sensor data from the treatment wellbore and/or sensor datafrom one or more monitoring wellbores spaced a distance apart from thetreatment wellbore, or combinations thereof. The modeling applicationpredicts a fracture propagation within the formation and produces apumping sequence. In an aspect, the modeling application can produce anupdated pumping sequence in real time during the fracturing job. Thepumping sequence can include two or more sub-stages, wherein themodeling application employs a first pumping routine model to provide afirst sub-stage of the pumping sequence and employs a second pumpingroutine model to provide a second sub-stage of the pumping sequence. Amanaging application controls the fracturing fleet in accordance withthe pumping sequence to place a fracturing fluid in the treatment well.

As described in detail herein, a method of monitoring a wellbore isprovided wherein one or more downhole sensors present in a wellboreprovides data gathered with regard to one or more conditions such aspressure and/or temperature within a formation and/or within a wellbore.Turning now to FIG. 1, illustrated is an embodiment of a wellsitemonitoring system 50 that can be utilized to gather wellbore data. Asdepicted, the wellbore 10 penetrates a subterranean formation 8 for thepurpose of recovering hydrocarbons. The wellbore 10 can be drilled intothe subterranean formation 8 using any suitable drilling technique. Thewellbore 10 extends substantially vertically away from the earth'ssurface 2 over a vertical wellbore portion 24, deviates from verticalrelative to the earth's surface 2 over a deviated wellbore portion 26,and transitions to a horizontal wellbore portion 28. In alternativeoperating environments, all or portions of a wellbore may be vertical,deviated at any suitable angle, horizontal, and/or curved. The wellbore10 may be a new wellbore, an existing wellbore, a straight wellbore, anextended reach wellbore, a sidetracked wellbore, a multi-lateralwellbore, and other types of wellbores for drilling and completing oneor more production zones. Further, the wellbore 10 may be used for bothproducing wells and injection wells. In an embodiment, the wellbore 10may be used for purposes other than or in addition to hydrocarbonproduction, such as uses related to geothermal energy or waste disposal.

In some embodiments, the wellbore 10 can be completed by cementing acasing string 14 (e.g., a conduit) within the wellbore 10 along all or aportion thereof. The cement 12 can be pumped down the interior of thecasing string 14, out a float shoe 20 (or other suitable primarycementing equipment), and into the annular space 22 (e.g., the annulus)between the casing string 14 and the wellbore 10. In other embodiments,however, the casing string 14 may be omitted from all or a portion ofthe wellbore 10, and the principles of the present disclosure canequally apply to an “open-hole” environment. In still other embodiments,however, the primary cementing equipment 20 at the end of the casingstring 14 can be drilled out, and a liner can be added to extend thelength of the wellbore.

The wellbore 10 can be drilled through the subterranean formation 8 to ahydrocarbon bearing formation 16, also referred to as the formation 16.Perforations 18 in the casing string 14 and cement 12 enable the fluidin the formation 16 to enter the casing string 14.

The cement 12 can have one or more wellbore sensors 30 positioned withinthe annular space 22 between the casing string 14 and the wellbore 10.The wellbore sensors 30 can include one or more wellbore fibers orcables 32, one or more electronic sensors 34, fiber optic sensors, microelectromechanical sensors (MEMS), or combinations thereof. The wellborefibers or cables 32 can be routed along the outside of the casing string14 and attached at various locations (e.g., at a coupling) with cableclamps known to the industry. The wellbore sensors 30 can be attached tothe casing string 14 with a casing clamp, attached to casing equipment,integrated within a sensor housing, or suspended along the casing. Insome embodiments, the wellbore sensors 30 can be wellbore cables 32containing distributed optical sensors such as fiber optic cables. Insome embodiments, the wellbore sensors 30 can be electronic sensors 34with wellbore cables 32 transmitting power and communicating data. Insome embodiments, the wellbore sensors 30 can be battery poweredelectronic sensors 34 transmitting data to the surface via sonar, radio,or audio telemetry. In some embodiments, the wellbore sensors 30 can bea combination of sensor types.

In an embodiment, the wellbore sensors 30 can be contained within (e.g.,distributed within) the cement. For example, a cement sheath can bedisposed within an annulus formed between a conduit disposed within thewell and a wall of the wellbore and the one or more sensors can comprisemicro electromechanical sensors (MEMS) disposed within the cementsheath, a fiber optic sensor disposed on the conduit (e.g., toread/interrogate the MEMS and/or convey data from the MEMS), or both.

In an embodiment, the wellbore sensors 30 can be located within anannular space without cement. The wellbore sensors 30 may be attached tothe casing string 14 along a portion of the casing string 14 withoutcement. The cement 12 may be isolated from a portion of the casingstring 14 by primary cementing equipment such as a cement basket, apacker cementing collar, or similar equipment known to the oilfield.

In an embodiment, the wellbore sensors 30 can be communicatively coupledwith the formation 16. The wellbore sensors 30 can gather data from theformation by direct contact or being communicatively connected to theformation 16 (e.g., acoustic energy, electromagnetic waves, radiation,etc. emanating from the wellbore into the surrounding formation).

In an embodiment, the wellbore sensors 30 can be communicatively coupledwith the interior 48 of the casing string 14. The wellbore sensors 30can gather data from the interior 48 of the casing string 14 by directcontact or be communicatively coupled with the inside diameter of thecasing string 14. Alternatively, the wellbore sensors 30 can be placedinside the casing string 14.

The data gathered by the wellbore sensors 30 can include mechanicalproperties such as stress or strain data, flow rate data, pressure data,temperature data, acoustic data, compositional data, or combinationsthereof. The wellbore sensors 30 can measure stress and strain from astrain-bridge mounted onto the outside surface or inside surface of thecasing string 14. The wellbore sensors 30 can measure pressure andtemperature at a discrete location within the cement isolation barrierand/or along a portion of the casing string 14. The wellbore sensors 30can measure the pressure and temperature of the formation 16. Thewellbore sensors 30 can measure data from the interior 48 of the casingstring 14. The wellbore sensors 30 may be a fiber optical sensor thatcan measure a distributed temperature along the fiber optical cable. Thewellbore sensors 30 may measure acoustic data from a discrete locationof an electronic sensor or along a distributed path of a fiber opticalcable. The wellbore sensors 30 may measure flow rate data from adiscrete location of an electronic sensor or from a discrete location ofan optical sensor.

A wellsite monitoring system 50 can include a production tree 40, a datalogging device 38, and a wired communication cable 44. The productiontree 40 can anchor the casing string 14 at surface 2. The productiontree 40 isolates the pressure within the casing string 14 and connects aproduction line to the well. The production tree 40 can also include oneor more production tree sensors 42 that gather pressure, temperature,and/or flowrate data. Although a production tree 40 is shown, any typeof pressure containment equipment connected to the top of the casingstring 14 may be used, such as a surface tree, subsea tree, lubricatorconnector, and blowout preventer. A data logging device 38 can gatherdata from the wellbore sensors 30 and the production tree sensor 42 forstorage and/or transmittal. A transmission cable 36 can pass through aproduction tree 40 to connect the data logging device 38 to the wellborecables 32. The data logging device 38 can communicate with the wellboresensors 30 and production tree sensor 42 via any suitable communicationmeans (e.g., wired, wireless, telemetry, etc.). The data can be gatheredin data sets based on a time interval. The data set can be retrievedfrom multiple wellbore sensors 30 and production tree sensors 42instantaneously or near instantaneously and logged with a time stamp.The data sets can be recorded in time intervals of milliseconds,seconds, minutes, hours, days, weeks, or months. The time intervals thatthe data sets are gathered by the wellbore sensors 30 and productiontree sensors 42 can change based on the wellbore conditions, user input,or by another application. The data logging device 38 can provide powerto and receive data from the wellbore sensors 30. The data loggingdevice 38 can contain an optical interrogator that transmits andreceives laser light to the wellbore cables 32 (e.g., fiber opticcables). The data logging device 38 can have a data storage deviceattached to or integrated within to store the data. The data loggingdevice 38 can store the data in transitory or non-transitory memory, inresident storage media, or in removable storage media. The data loggingdevice 38 can store the data or transmit the data for analysis. The datalogging device 38 can transmit the data via wireless communication 46(e.g., a transceiver) or a wired communication cable 44.

As described in detail herein, a method of controlling a pumpingsequence of a fracturing fleet at a wellsite by a managing applicationwhile monitoring equipment data provided by sensors on the fracturingunits indicative of a pumping stage of the pumping sequence. Turning nowto FIG. 2, illustrated is an embodiment of a hydraulic fracturing system100 that can be utilized to pump hydraulic fracturing fluids into awellbore. As depicted, a plurality of hydraulic fracturing pumps 122(also referred to as “frac pumps” or high horsepower pumps) is connectedin parallel to a fracturing manifold 124 (also referred to as a“missile”) to provide fracturing fluids to the treatment well 130. Thefracturing fluids are typically a blend of gelled fluid (e.g., water, agelling agent, optionally a friction reducer and/or other additives) andproppant. The gelled fluid is created in the hydration blender 114 withwater from the water supply unit 112 and gelling chemicals from thechemical unit 116. The proppant is added at a controlled rate to thegelled fluid in the mixing blender 120 and pumped into the manifold 124for distribution to the frac pumps 122 by feedlines 126. Althoughfracturing fluids typically contain a proppant, a portion of the pumpingsequence may include a fracturing fluid without proppant (sometimesreferred to as a pad fluid or slick water, for example comprising waterand a friction reducer). Although fracturing fluids typically include agelled fluid, the fracturing fluid may be blended without a gellingchemical. Alternatively, the fracturing fluids can be blended with anacid to produce an acid fracturing fluid, for example, pumped as part ofa spearhead or acid stage that clears debris that may be present in thewellbore and/or fractures to help clear the way for fracturing fluid toaccess the fractures and surrounding formation. Although the frac pumps122, hydration blender 114, chemical unit 116, and mixing blender 120are typically diesel powered, these frac units and others can be dualfuel (e.g., diesel and/or natural gas), electrically powered with anelectric generator, electrically powered with batteries, or anycombination thereof.

A control van 110 can be communicatively coupled (e.g., via a wired orwireless network) to any of the frac units wherein the term “frac units”may refer to any of the plurality of frac pumps 122, a manifold 124,mixing blender 120, proppant storage unit 118, hydration blender 114,water supply unit 112, and chemical unit 116. The managing application136 executing on a computer (e.g., server) 132 within the control van110 can establish unit level control over the frac units communicatedvia the network. Unit level control can include sending instructions tothe frac units and/or receiving equipment data from the frac units. Forexample, the managing application 136 within the control van 110 canestablish a pump rate of 25 bpm with the plurality of frac pumps 122while receiving pressure and rate of pump crank revolutions from sensorson the frac pumps 122.

The managing application 136 within the control van 110 can becommunicatively coupled to one or more wells located a distance fromtreatment well 130, for example communicatively coupled to a remotewellsite 138 and a remote wellsite 140. A managing application 136 canreceive data from the data logging device 38 at the remote wellsite 138and the remote wellsite 140. Although two well sites are shown, themanaging application 136 can be communicatively coupled to 1, 2, 3, 4,5, 10, 15, 20, or any number of data logging devices attached to remotewell sites (e.g., data logging device 38 at remote wellsite 138 and/or140).

The control van 110 can have a modeling application 146 executing on thesame computer (e.g., server) 132 or on a second computer 142. Themodeling application 146 can receive data from the data logging device38 at the treatment well 130, at the remote or monitoring wellsite 138and/or 140, or combinations thereof. The modeling application 146 canmodel the fracture propagation from the pumping sequence based on thedata received from the treatment well 130, from the remote wellsites 138and/or 140, or combinations thereof as described in more detail furtherhereinafter.

Although the managing application 136 and modeling application 146 aredescribed as executing on a computer 132/142, it is understood that thecomputer 132/142 can be a computer system or any form of a computersystem such as a server, a workstation, a desktop computer, a laptopcomputer, a tablet computer, a smartphone, or any other type ofcomputing device. The computer 132/142 (e.g., computer system) caninclude one or more processors, memory, input devices, and outputdevices, as described in more detail further hereinafter, for example,with reference to FIG. 15. Although the control van 110 is described ashaving the managing application 136 executing on a computer 132, it isunderstood that the control van 110 can have 2, 3, 4, or any number ofcomputers 132 (e.g., computer systems) with 2, 3, 4, or any number ofapplications (e.g., managing application 136 and modeling application146) executing on the computer 132.

In some embodiments, the hydraulic fracturing system 100 can include aninstrumented package 102 coupled to one or more frac units, for example,to isolate one or more frac units upon receipt of a computerizedcommand. The instrumented package 102 can be communicatively coupled tothe managing application 136 within the control van 110. Turning to FIG.2B, an instrumented package 102, is illustrated. The instrumentedpackage 102 can include one or more isolation valves 104 and sensorsthat measure data at a periodic rate such as milliseconds, seconds,minutes, hours, days, and months. The isolation valve 104 is typically aplug valve that can be manual, hydraulic, electrical, or pneumaticoperated. Although one isolation valve 104 is shown, two or moreisolation valves 104 may be used. The instrumented package 102 caninclude sensors to measure temperature, pressure, flow rate, density,viscosity, vibration, strain, accelerometers, exhaust, acoustic,position, and identity. For example, a pressure transducer 106 can beconfigured to measure the pressure in pounds per square inch (psi). Aflow rate sensor 108 can be a turbine, differential, ultrasonic,Coriolis, or any other type of flow meter configured to measure inbarrels per minute (bpm). A weight sensor can measure proppant by theweight of material added. For example, the rate that proppant is addedto the fracturing fluids can be measured by pounds per gallon (ppg). Theperiodic data can be communicated to the control van 110. In someembodiments, the managing application 136 within the control van 110 canremotely operate one or more isolation valves 104 in the instrumentedpackage 102 to the open or closed position. In an aspect, the isolationvalve 104 is has a fail-safe in a closed position, such that the valvecloses in the event of a loss of communication from control van 110.

Turning now to FIG. 3, an example of unit level control of the fracunits is illustrated. As an example, the water supply unit 112 includesa water supply tank 148, a unit control module 150, a unit sensor module152, a water supply pump 156, and a pipeline 160. The water supply unit112 can further comprise an instrumented package 102, for example, inpipeline 160. The unit control module 150 (e.g., microprocessorcontroller) is in communication with and can operate the water supplypump 156, an isolation valve 158, and the instrumented package 102. Theunit sensors module 152 is in communication with and can receiveperiodic sensor data from various sensors including temperature,pressure, flow rate, density, viscosity, chemical, vibration, strain,accelerometers, exhaust, acoustic, fluid level, equipment identity, andany other sensors typically used in the oilfield. The sensors canmeasure data at a periodic rate such as milliseconds, seconds, minutes,hours, days, and months. For example, the unit sensor module 152 canreceive periodic data from a water level sensor 154. The managingapplication 136 within the control van 110 can establish unit levelcontrol of the water supply unit 112 by communicatively connected to theunit control module 150 and the unit sensor module 152. The managingapplication 136 within the control van 110 can control the isolationvalve 158, water supply pump 156, and/or the instrumented package 102via the unit control module 150. The control van 110 can monitor theequipment data, such as water level and flow rate, via unit sensormodule 152. Although the water supply unit 112 is shown, all of the fracunits can have a unit control module 150 and unit sensor module 152 suchas the hydration blender 114, the chemical unit 116, the proppantstorage unit 118, the mixing blender 120, the manifold 124, and theplurality of frac pumps 122. The managing application 136 within thecontrol van 110 can direct the frac fleet, illustrated in FIG. 2A, toprepare a fracturing fluid having a desired composition and pump thefrac fluid at a desired pressure and flow rate.

In an aspect, one or more frac units of the frac fleet can be connectedto the treatment well 130 at a production tree of the treatment well130. For example, a wellhead isolation tool can connect the manifold 124to the production tree. The wellhead isolation tool and production treecan include a unit sensor module (e.g., 152) with one or more surfacesensors, downhole sensors, and associated monitoring equipment. Thesensors on surface frac units can measure the equipment operationalconditions including temperature, pressure, flow rate, density,viscosity, chemical, vibration, strain, accelerometers, exhaust,acoustic, fluid level, and equipment identity. Sensors on the wellheadisolation tool and production tree can measure the environment insidethe treatment well including temperature, pressure, flow rate, density,viscosity, chemical, vibration, strain, accelerometers, and acoustic. Inan aspect, one or more frac units of the frac fleet can connect to thetreatment well 130 with a wellhead isolation tool, a wellhead, aproduction tree, a drilling tree, or a blow out preventer.

In an aspect, one or more frac units of the frac fleet can be downholetools communicatively connected to the control van 110. For example, afrac sleeve with downhole sensors can be communicatively connected tothe production tree and wellhead isolation equipment. In another aspect,a hydrojetting, perforating gun, or other perforating tool deployeddownhole via a wireline or coiled tubing unit as part of a perf and fracoperation, and one or more sensors may be associated with the surfaceand/or subsurface equipment associated with such an operation. Thedownhole sensors can include wellbore cables, electronic sensors, fiberoptic sensors, and other types of downhole sensors that measure thewellbore environment. The downhole sensors can connect to a unit sensormodule (e.g., 152) communicatively connected to the control van 110. Thedownhole tools can connect to a unit control module communicativelyconnected to the control van 110.

A method for creating and/or modifying a pumping sequence for pumpingthe frac fluid into a wellbore to propagate fractures into a formationis described. The method can be used to establish a pumping sequence(e.g., an initial pumping sequence) in preparation for a pumpingoperation associated with a fracturing job. The method can also be usedduring the pumping operation to modify the pumping sequence in real time(e.g., after the start of and prior to the end of the pumping operation)based on sensor data (e.g., surface and/or subsurface data) from one ormore well sites. Turning now to FIG. 4, the hierarchy of a method fordeveloping a pumping sequence is illustrated and includes a fracturemodeling control component 164, a pumping sequence control component166, a supervisory control component 168, a plurality of unit controlcomponents 170, and a plurality of surface and/or subsurface datasensors providing associated sensor data. The fracture modeling controlcomponent 164 can model fracture propagation within a formation based onvarious inputs and determine a pumping sequence to generate thefractures. The pumping sequence can include a series of steps, alsocalled stages, with one or more defined frac fluid pump rates andapplied pumping pressure (e.g., a ramp up flow rate, a steady state flowrate, and a ramp down flow rate for each stage) for one or more fracfluids used in a stage (e.g., acid fluids, pad fluids, slick water,proppant laden fluids, water, etc.). The fracture modeling controlcomponent 164 can model fracture propagation during a pumping operationwith sensor data 174 from the treated wellbore (e.g., sensor data fromthe wellsite monitoring system 50 in FIG. 1 that includes subsurfacedata collected from the wellbore and/or surface data that may becollected from the fracturing spread of FIG. 2A via unit sensors module152, as shown in FIG. 3). The fracture modeling control component 164can also use the sensor data 172 and/or sensor data 176 from one or moreremote, monitoring well sites (e.g., well site 138 & 140 in FIG. 2 thatmay be equipped with a wellsite monitoring system 50 of the typedescribed with reference to FIG. 1) to model fracture propagation duringa pumping operation. The fracture modeling control component 164 cancompare in real time the sensor data generated by the wellsitemonitoring system 50 of the treatment well 130 during the pumpingoperation to the pumping sequence, and the fracture modeling controlcomponent 164 can make adjustments to the pumping sequence in real timeas needed. The fracture modeling control component 164 can be themodeling application 146 executing on the second computer 142 shown inFIG. 2A and/or the fracture modeling control component 164 can be themodeling application 224 executing on the computer 222 at service center220. The fracture modeling control component 164 can also determine aninitial pumping sequence (e.g., a start of the frac job or start ofstage pumping sequence) based on inputs such as wellbore geometry,formation geo-mechanical properties, the number of zones, fluidproperties, and other criteria. Also, the pumping sequence (e.g.,initial pumping sequence) can be optimized based on customer input suchas one or more of the cost of each fracturing stage, the total cost ofthe fracturing job, a noise emission limit, a greenhouse gas emissionstarget, a fuel consumption target, a proppant volume target for eachfracturing stage, a proppant volume target for the fracturing job, ausage limit of one or more chemicals present in the fracturing fluidused in each fracturing stage, a usage limit of one or more chemicalspresent in the fracturing fluid used in the fracturing job, or anycombination thereof. The pumping sequence and modeled fracturepropagation, also called a fracture model, can be sent from the fracturemodeling control component 164 to the pumping sequence control component166 for further processing. In an aspect, the fracture modeling controlcomponent 164 includes fracture propagation prediction software such asSmartFleet, available from Halliburton, which can include pumpingsequence creation. In an aspect, the fracture modeling control componentmay employ one or more sub-models (and/or the fracture modeling controlcomponent may comprise of a plurality of fracture modeling modules), forexample, as shown at blocks 910A-Z and described with reference to FIG.11.

The pumping sequence control component 166 can convert the pumpingsequence to an automated pumping sequence to direct the supervisorycontrol component 168 through each pumping stage. The automated pumpingsequence includes instructions for unit level control of each frac unit.The supervisory control component 168 can direct the unit controlcomponents 170A-Z to communicate the commands and instructions to theunit control module of each frac unit such as unit control module 150 ofthe water supply unit 112 shown in FIG. 3. The supervisory controlcomponent 168 may direct two or more frac units to work in concert withthe same instructions given to each frac unit. For example, thesupervisory control component 168 can instruct the unit control 170A-Zto direct two or more frac pumps 122 to operate at the same pump rate.The supervisory control component 168 can direct one or more frac unitsto operate within the same limits. For example, the supervisory controlcomponent 168 can instruct the one or more unit controls 170A-Z todirect the mixing blender 120 to supply frac fluid via feedlines 126 tothe plurality of frac pumps 122 at the same flow rate as the frac pumps122 are pumping. The pumping sequence control component 166 may be themanaging application 136 executing on a computer 132 within control van110. An operator in the control van 110 may install an automated pumpingsequence (e.g., received from modeling application 224 or 146) into thepumping sequence control component 166 for example, the managingapplication 136 executing on the computer 132 within control van 110. Inan aspect, the pumping sequence control component 166 includes frac unitmanagement software such as Automated Fleet available from Halliburton,which can include unit level control software.

The fracture modeling, pump sequence, and automated pump sequence can bedeveloped locally at the wellsite or remotely from the wellsite andconveyed or transmitted to the wellsite. The pump sequence can bemodified based on sensor data from a monitored wellsite that can betransmitted by various wired or wireless means for further processing.For example, data can be transmitted and received by various wired orwireless means between a service center and the control van 110 at aremote wellsite location for further processing and/or use in modeling.Turning now to FIG. 5, a data communication system 200 is described. Thedata communication system 200 comprises a wellsite 202 (where thefracturing spread of FIG. 2A can be located), an access node 210, one ormore monitored wellsites 216, one or more access nodes 210 (e.g.,cellular site), one or more networks 212, one or more storage computers214, one or more service centers 220, a plurality of user devices 226,and one or more customer devices 228. A wellsite 202 can include acontrol van 204 as part of a frac fleet (e.g., control van 110 of FIG.2A) pumping a frac fluid into the wellhead (e.g., treatment well 130 inFIG. 2A). The control van 204 can be communicatively coupled to themonitored wellsite 216, storage computer 214, and service center 220 bya communication device 206 (e.g., transceiver) that can transmit andreceive via any suitable communication means (wired or wireless) forexample, wirelessly connect to an access node 210 to retrieve data(e.g., pumping sequence) from a storage computer 214. The monitoredwellsite 216 can have a communication device 218 (e.g., transceiver)that can be communicatively coupled by wired or wireless means to thecontrol van 204, storage computer 214, or service center 220. Thestorage computer 214 may also be referred to as a data server, datastorage server, or remote server. Wireless communication can includevarious types of radio communication, including cellular, satellite 215,or any other form of long range radio communication. For example,communication device 206 on the control van 204 can wirelessly connectto access node 210 that is communicatively connected to a network 212.The network 212 can be one or more public networks, one or more privatenetworks, or a combination thereof. A portion of the Internet can beincluded in the network 212. The storage computer 214 can becommunicatively connected to the network 212. The service center 220 canhave one or more computers 222 communicatively connected to the network212.

The service center 220 can have a modeling application 224 and amanaging application 225 executing on one or more computers 222. Apumping sequence associated with a wellbore fracturing job can bedetermined from fracture modeling performed by a fracture modelingapplication 224 executing on computer 222. A user device 226 can receivea customer request for a fracturing job (e.g., comprising a pumpschedule) with various customer inputs from a customer device 228. Thecustomer inputs may include formation properties, a number of zones,well completion information, well logs, a well survey, or combinationsthereof. The modeling application 224 can predict the propagation offractures within a given formation penetrated by a wellbore based on themechanical properties of the formation and rheologic properties of thefracturing fluid. These formation mechanical properties may be based onrock cores, survey data, or determined from previous fracturingoperation performed in the same field. The modeling application 224executing on a computer 222 can produce a pumping sequence based on thedesired fracture propagation. In an aspect, the fracture modelingcontrol component 164 includes fracture propagation prediction softwaresuch as SmartFleet, available from Halliburton, which can includepumping sequence creation. The modeling application 224 can send thepumping sequence to the storage computer 214 via network 212. Likewise,the modeling application 224 can send the pumping sequence to thecontrol van 204 via the network 212, the access node 210, and thecommunication device 206.

An automated pumping sequence can be created from the pumping sequencemodeled by the fracture modeling application 224. The automated pumpingsequence can be created by the fracture modeling application 224 oranother application (e.g., managing application 225) and saved tostorage computer 214 and/or transmitted to the control van 204 at thewellsite 202. For example, a user device 226 can be used to direct themanaging application 225 to create an automated pumping sequence fromthe pumping sequence. The managing application 225 can retrieve thepumping sequence from the storage computer 214 via the network 212. Themanaging application 225 can retrieve the pumping sequence from thecontrol van 204 via the network 212 and access node 210. The managingapplication 225 can also retrieve the pumping sequence from the computer222 within the service center 220. The automated pumping sequence can becreated from the pumping sequence and saved to storage computer 214 ortransmitted to the control van 204 at the wellsite 202.

Although the fracture modeling application 224 is described as executingon a central computer 222, it is understood that the central computer222 can be a computer system or any form of a computer system such as aserver, a workstation, a desktop computer, a laptop computer, a tabletcomputer, a smartphone, or any other type of computing device. Thecentral computer 222 (e.g., computer system) can include one or moreprocessors, memory, input devices, and output devices, as described inmore detail further hereinafter. Although the service center 220 isdescribed as having the fracture modeling application 224 executing on acentral computer 222, it is understood that the service center 220 canhave 2, 3, 4, or any number of computers 222 (e.g., computer systems)with 2, 3, 4, or any number of modeling applications 224 or secondapplications 225 (e.g., managing application) executing on the centralcomputers 222.

In an aspect, the network 212 includes a 5G core network with virtualservers in a cloud computing environment. One or more servers of thetype disclosed herein, for example, storage computer 214 and centralcomputer 222, can be provided by a virtual network function (VNF)executing within the 5G core network. In an aspect, the access node 210can be referred to as a gigabit Node B (gNB) of 5G technologygeneration. In some contexts, the access node 210 can be referred to asa cell site or cell tower, as will be discussed further hereinafter. Thecontrol van 204 on the wellsite 202 can be communicatively coupled tothe network 212 which includes the 5G network via the access node 210(e.g., gigabit Node B) and thus can be communicatively coupled to one ormore VNFs with virtual servers as will be more fully describedhereinafter, for example with reference to FIGS. 14A and 14B.

A pumping sequence may be associated with a pumping stage, and eachpumping stage may be separated into a series of pumping sub-stages(e.g., scripts) as a function of time having one or more transitionsbetween each pumping sub-stage. Turning now to FIG. 6A, a pumpingsequence, which may also be referred to as a pumping schedule or aplurality of successive time-dependent pumping intervals, 300 isillustrated. The pumping sequence is illustrated as a graph of pressure,flow rate, and proppant density as a function of time. The chartincludes a pressure axis 302 with units of pounds per square inch (psi),flowrate axis 304 with units of barrels per minute (bpm), a proppantaxis with units of pounds per gallon (ppg), and a horizontal axis oftime with units of seconds, minutes, or hours. The graph of the pumpingsequence 300 includes a pressure plot line 310, flowrate plot line 312,and proppant plot line 314 for a single zone hydraulic fracturingtreatment. A fracturing job can include treatment for 2, 3, 4, 5, 10,20, 40, 80, or any number of zones, and a corresponding number ofpumping sequences 300 of the type illustrated in FIG. 6A can be used.Although the pumping sequence 300 illustrated in FIG. 6A shows atreatment of a single fracturing zone within the wellbore (which mayalso be referred to as a single stage), the pumping sequence 300 caninclude other pumping operations including pressure testing ofindividual pumps, removing air from pumping equipment and pressurelines, pressure testing the pumping system, a rate controlled zonaltreatment, a chemical treatment without proppant, releasing a divertertreatment, and treatment pumping with pressure limits. The pumpingsequence 300 can include one or more pumping operations within eachstage or zone treated.

Turning now to FIG. 6B, the pumping sequence 300 can be broken up intopumping sub-stages containing steady sub-stages and transitionsub-stages. The first sub-stage 320 is a transition sub-stage in thepumping sequence 300 where the pressure plot line 310, flowrate plotline 312, and proppant plot line 314 are increasing in value. Thetransition sub-stages can be a smooth plotline (e.g., 310 & 312),indicating an approximate steady increase in pressure and flowrate or astepped increase (e.g., 314) indicating an incremental increase inproppant density. The second sub-stage 322 can be a steady sub-stagewhere the pumping rate remains steady or relatively unchanged. Thepressure plot line 310, flowrate plot line 312, and proppant plot line314 are steady in value. The third sub-stage 324 can be a transitionsub-stage where the plotlines are decreasing in value to another steadystate sub-stage. The fourth sub-stage 326 can be a steady sub-stagewhere the pumping rate remains steady. Although seven pumping sub-stagesare shown, the pumping sequence 300 can include 10, 20, 30, 40, 50, orany number of pumping sub-stages without deviating from this disclosure.

The pumping sequence 300 can be written (e.g., coded as software) as anautomated pumping sequence 350 comprising a set of instructions in ascripting language for execution by managing application 136. Turningnow to FIG. 7 with reference to FIG. 4, the automated pumping sequence350 can include an automated script for each pump stage with multipleinstructions (e.g., commands) for each frac unit. The automated scriptmay comprise multiple instructions written in a high level programminglanguage or scripting languages such as Python, Java, Perl, Ruby, Tcl,or Smalltalk. The term instruction includes a command, multiplecommands, and/or a line of script (e.g., high level programminglanguage) that can contain one or more instructions. This type of highlevel programming language may include instructions that control thehardware function (e.g., open, close, on, off, etc.), firmware, andsoftware.

A sub-stage script may be written for each pumping sub-stage. Forexample, the first sub-stage script 352 in FIG. 7 may be an automaticpumping script for the first sub-stage 320 in FIG. 6B. The secondsub-stage script 354 in FIG. 6 may be the automatic script written forthe second sub-stage 322 in FIG. 6B. The third sub-stage script 356 maybe the automatic script written for the third sub-stage 324 in FIG. 6B.Within each sub-stage script (e.g., first sub-stage script 352), a unitscript 360 A-Z may be written for the unit control 170A-Z of each fracunit. For example, with reference to FIG. 3, the automated unit script360A can instruct the unit control module 150 of the water supply unit112 within the first sub-stage script 352. The supervisory controlcomponent 168 can link the instructions to two or more unit scripts360A-Z with a supervisory link 362. Although three sub-stage scripts andthree pumping sub-stages are described, a sub-stage script can becreated for 3, 5, 10, 20, 50, 100, or any number of sub-stages withoutdeviating from the disclosure.

The first sub-stage script 352 can be written to idle the frac units,pressure test the frac units, to prime the equipment (e.g., add water tothe equipment linking pipelines), increase the pump rate, increase afluid density, add a chemical to fluid flow, establish a desired pumprate, decrease the pump rate, decrease a fluid density, drop amechanical device into the well, cease the pumping operation, or anycombination thereof. The first sub-stage script 352 can also be writtento establish the frac units available on the wellsite based on a uniqueidentifier associated with each unit (e.g., an identification numberencoded within an RFID tag, a bar code, etc.).

With reference to FIGS. 8-11, embodiments of a method for creatingand/or modifying a pumping sequence for pumping the frac fluid into awellbore to propagate fractures into a formation are described. Themethod can be used to establish a pumping sequence (e.g., an initialpumping sequence) in preparation for a pumping operation associated witha fracturing job. The method can also be used during the pumpingoperation to modify the pumping sequence in real time (e.g., after thestart of and prior to the end of the pumping operation) based on sensordata (e.g., surface and/or subsurface data) from one or more well sites.

With reference to FIGS. 8-11, disclosed herein are methods ofcontrolling a pumping sequence of a fracturing fleet at a wellsite whileperforming a fracturing job on a treatment wellbore penetrating asubterranean formation. A modeling application receives one or more userinputs related to the fracturing job, one or more equipment inputscomprising sensor data from one or more frac units of the fracturingfleet, one or more wellbore inputs comprising sensor data from thetreatment wellbore and/or sensor data from one or more monitoringwellbores spaced a distance apart from the treatment wellbore, orcombinations thereof. The modeling application predicts a fracturepropagation within the formation and produces a pumping sequence. In anaspect, the modeling application can produce an updated pumping sequencein real time during the fracturing job. The pumping sequence can includetwo or more sub-stages, wherein the modeling application employs a firstpumping routine model to provide a first sub-stage of the pumpingsequence and employs a second pumping routine model to provide a secondsub-stage of the pumping sequence. A managing application controls thefracturing fleet in accordance with the pumping sequence to place afracturing fluid in the treatment well.

Turning now to FIG. 8, the method 800 for creating a pumping sequence(e.g., an initial pumping sequence) is described with a logical flowdiagram. At block 802, a set of customer inputs are entered intomodeling application 224 or 146 from a user device 226. The customerinputs can include a desired or target fracture profile, formationproperties, number of zones, type of perforations, fracture geometry,well geometry, well completion information, a well survey, well logs andother associated criteria. The formation properties can includemechanical properties based on rock cores, survey data, and/ordetermined from previous hydraulic fracturing operations. The customerinputs can also include optimization targets such as one or more of thecost of each fracturing stage, total cost of the fracturing job, a noiseemission limit, a greenhouse gas emissions target, a fuel consumptiontarget, a proppant volume target for each fracturing stage, a proppantvolume target for the fracturing job, a usage limit of one or morechemicals present in the fracturing fluid used in each fracturing stage,a usage limit of one or more chemicals present in the fracturing fluidused in the fracturing job, reservoir production targets, formationfracture geometry/profile targets, cost targets, exhaust emissiontargets, acoustic/noise targets, or any combination thereof. At block804, the modeling application 224/146 (e.g., fracture modeling controlcomponent 164) can predict the propagation of fractures within a givenformation (e.g., model the fractures) based on the targets inputted,such as the mechanical properties of the formation and rheologicalproperties of the fracturing fluid. At block 806, the modelingapplication 224/146 can produce a pumping sequence (e.g., an initialpumping sequence) based on the desired fracture propagation. The pumpingsequence can be a pumping sequence for the wellbore or a portion of thewellbore, for example an initial pumping sequence that will be used atthe start of a fracturing job or operation. For example, the modelingapplication 224/146 can produce a pumping sequence for one or morestages of a fracturing job or operation such as shown in FIGS. 6A and6B.

At block 808, the modeling application 224/146 can determine if thepumping sequence is optimized by comparing the pump schedule to thetarget fracture profile and optimization targets for a given fracturingjob for a given customer. If the pumping sequence is not optimized(e.g., exceeds an optimization threshold for one or more targetvariables such as cost, noise, the pumped volume of fracturing fluidcomponent(s), production rate, fracture profile, etc.), the modelingapplication 224/146 can return to block 802 and iterate the targetinputs. The modeling application 224/146 may ask the user for new inputsat block 802 if iterating the target inputs exceeds a range for targetinputs (e.g., exceeds a maximum or minimum value for one or more targetvariables such as cost, noise, pumped volume of fracturing fluidcomponent(s), production rate, fracture profile, etc.). The modelingapplication 224/146 can proceed to block 810 if the pumping sequence isoptimized (e.g., within an optimization threshold for a given set oftarget variables). At block 810, the modeling application 224/146 cansend the pumping sequence to the managing application 225/136. Theautomatic pumping sequence can be produced by the managing application225/136 from the pumping sequence, for example in accordance with thedisclosure of co-pending U.S. application Ser. No. ______, entitled“Method for Equipment Control” (attorney docket number 4727-10800),filed concurrently herewith and incorporated herein by reference in itsentirety.

In an embodiment, the method 800 can use modeling application 146executing on the computer 142 within the control van 110 to produce apumping sequence (e.g., an initial pumping sequence) as disclosedherein, for example with reference to FIG. 8. The managing application136 executing on computer 132 within the control van 110 can receive thepumping sequence from the modeling application 146 to produce theautomated pumping sequence.

In an embodiment, the method 800 can use modeling application 224executing on the computer 222 within the service center 220 to producepumping sequence (e.g., an initial pumping sequence) as disclosedherein, for example with reference to FIG. 8. The managing application136 executing on computer 132 within the control van 110 can receive thepumping sequence from the modeling application 224 or from the storagecomputer 214 via network 212 to produce the automated pumping sequence.

In an embodiment, the method 800 can use modeling application 224executing on the computer 222 within the service center 220 to producepumping sequence (e.g., an initial pumping sequence) as disclosedherein, for example with reference to FIG. 8. The managing application225 executing on computer 222 within the service center 220 can receivethe pumping sequence from the modeling application 224 to produce theautomated pumping sequence, which can be saved in storage computer 214and/or provided via network 212 to managing application 136 executing oncomputer 132 at control van 110.

In an embodiment, the method 800 can use modeling application 146executing on the computer 142 within the control van 110 to produce apumping sequence (e.g., an initial pumping sequence) as disclosedherein, for example with reference to FIG. 8. The modeling application146 can send the pumping sequence to storage computer 214 via network212. The managing application 136 executing on computer 132 within thecontrol van 110 can receive the pumping sequence from the modelingapplication 224 or from the storage computer 214 via network 212 toproduce the automated pumping sequence.

In an embodiment, the method 800 can use modeling application 146executing on the computer 142 within the control van 110 to produce apumping sequence (e.g., an initial pumping sequence) as disclosedherein, for example with reference to FIG. 8. The modeling application146 can send the pumping sequence to storage computer 214 via network212. The managing application 225 executing on computer 222 within theservice center 220 can receive the pumping sequence from the storagecomputer 214 and produce the automated pumping sequence, which can besaved in storage computer 214 and/or provided via network 212 tomanaging application 136 executing on computer 132 at control van 110.

A method for modifying a pumping sequence in real time during a pumpingoperation to achieve the desired, targeted fracture propagation isdescribed. Turning now to FIG. 9, the method 820 for modifying a pumpingsequence is described with a logical flow diagram. At block 822, thepumping sequence can be loaded into the modeling application 146executing on the computer 142 within the control van 110. The associatedautomated pumping sequence (e.g., the automated pumping sequencecorresponding to the pumping sequence uploaded to the modelingapplication 146) can be loaded into the managing application 136 on thecomputer 132 within the control van 110. In an aspect, modelingapplication 146 and managing application 136 can be executing on thesame computer or server. At block 824, the targets for one or moreparameters of a stage of the pumping sequence are identified ordetermined from the pumping sequence by the modeling application 146 oralternatively, the targets for one or more parameters of a stage of thepumping sequence are loaded into the modeling application 146.

The method 820 can execute an automated sub-stage routine 848 during apumping stage of the automated pumping sequence. One or more automatedsub-stage routines 848 can execute during a pump stage based oninstructions present in the automated pumping script and/or based onoperational feedback provided by sensor data 828. For example, theautomated pumping script may have an automated sub-stage routine 848 toexecute during a pumping stage. In another example, the modelingapplication 146 can add an automated sub-stage routine 848 to thepumping sequence based on operational feedback provided by sensor data828.

The automated sub-stage routine 848 begins with the initiation of asub-stage routine at block 826. The sub-stage routine can correspond toa sub-stage of a pumping sequence 300, as shown in FIGS. 6A and 6B, andmay comprise set point or target values for parameters associated withthe pumping stage such as pumping pressure, pumping flow rate, proppantamount, the composition of the fracturing fluid, or combinationsthereof. The sub-stage routine may be a control routine for a pluralityof unit level components (e.g., frac units as shown in FIG. 2A)associated with a pumping stage, for example, a pump routine, a proppantramp routine, a proppant placement routine, a chemical placementroutine, a formation conductivity routine, a blender routine, adiversion product drop routine, or combinations thereof. For example, atblock 826, sub-stage 1 of the pumping sequence 300 of FIG. 6B may beginby blending a fracturing fluid in accordance with the sub-stage 1 scriptand ramping up the pumping of the fracturing fluid into the wellbore inaccordance with the profile shown in FIG. 6B. In an aspect, the identityof the unit level component of the frac spread (e.g., frac units asshown in FIG. 2A) can be determined automatically, for example, inaccordance with the disclosure of co-pending U.S. application Ser. No.______ entitled “Method for Equipment Control” (attorney docket number4727-10800), filed concurrently herewith and incorporated herein byreference in its entirety.

At block 830, the modeling application 146 receives sensor data 828,which may include (A) sensor data 174 from the treated wellbore, whichmay further include (i) sensor data from the wellsite monitoring system50 in FIG. 1 that includes subsurface data collected from the wellboreand/or surrounding formation; (ii) surface data that may be collectedfrom the fracturing spread of FIG. 2A via unit sensors 152 as shown inFIG. 3); or (iii) both (i) and (ii); (B) sensor data 172 and/or sensordata 176 from one or more remote, monitoring well sites 138 and/or 140,respectively, as shown in FIG. 2A, which may further include subsurfacesensor data collected from with a wellsite monitoring system 50 of thetype described with reference to FIG. 1 installed at wellsite 138 and/or140 in FIG. 2A; or (C) both (A) and (B). The modeling application 146can use the sensor data 828 to determine a current or real time state ofthe model, which may correspond to a current or real time parameter ofthe pumping sequence (e.g., pressure, flow rate, proppant amount fracfluid composition, etc.), a current or real time parameter of thefractures in the formation (e.g., size, number, geometry, etc. offractures), or combinations thereof. The modeling application 146 mayfurther compare the current or real time state of the model (andcorrespondingly one or more current or real time parameters of thepumping sequence and/or formation fracture profile) to an expected orpredicted state of the model to identify any differences betweenexpected/predicted/target values of parameters and current/real timevalues of parameters associated with the pumping sequence and/orformation fracture profile.

If one or more of the current or real time parameters of the fracturingjob derived from sensor data 828 deviate from the correspondingtarget/predicted parameters by more than a predefined delta, theautomated sub-stage routine 848 proceeds to block 834 for exceptionhandling. In an aspect, the automated stage routine determines at block834, whether an exception script corresponding to the present exceptionis present and available for execution. The exception script at block834 can be a script of instructions (e.g., commands) to change theoperation of the pumping stage to address (e.g., correct) the exception.In an aspect, the exception script is an automated exception script, forexample, in accordance with the disclosure of co-pending U.S.application Ser. No. ______, entitled “Method for Equipment Control”(attorney docket number 4727-10800), filed concurrently herewith andincorporated herein by reference in its entirety. Upon execution, theexception script at block 834 can proceed to block 836 to modify (e.g.,automatically and/or via user input) one or more stage targets andthereby provide a corresponding one or more modified stage targets. Ifthe modified stage targets are within a predefined range (e.g., withinthe acceptable ranges of corresponding values used to develop theinitial pumping sequence), the exception script at block 834 returns toblock 826 with the modified stage targets. If the modified stage targetsare outside a predefined range, the exception script will proceed toblock 838 to notify the user (e.g., service personnel) of an exception.At block 838, the automated sub-stage routine 848 notifies the users ofan exception and returns control or partial control to the user. Theuser can perform any or all of the mitigating steps including manuallysetting one or more new or modified stage targets, terminating theautomated sub-stage routine 848, ending the active pumping stage, ormanually controlling the frac fleet.

Returning to block 832, if one or more of the current or real timeparameters of the fracturing job derived from sensor data 828 does notdeviate from the corresponding target/predicted parameters by more thana predefined delta, the automated sub-stage routine 848 proceeds toblock 832. At block 832, the automated sub-stage routine 848 checks tosee if one or more target values of the pumping stage have been met, forexample a given pressure, flow rate, proppant amount, frac fluidcomposition, or a combination thereof for the stage. If one or moretarget values of the pumping stage have not been met, the automatedsub-stage routine 848 returns to block 826. If the target values of thepumping stage have been met, the automated sub-stage routine 848proceeds to block 840.

At block 840, the modeling application 146 checks to see if a stage hasbeen completed. If the pumping stage has not finished, the modelingapplication 146 can return to block 824 and the pumping of fracturingfluid associated with the present stage can be continued. If the pumpingstage has been completed, the modeling application 146 can proceed toblock 842. At block 842, the modeling application 146 can report out thedata (e.g., sensor data 828) and results of the completed pumping stageand proceed to block 844. At block 844, the modeling application 146checks to see if all of the pumping stages have been completed for agiven pumping sequence (e.g., determine whether the fracturing job iscomplete). If the pumping sequence has not finished, the modelingapplication 146 can return to block 822 and the fracturing job proceedswith pumping of the next stage. If the pumping sequence has completedall of the pumping stages (e.g., the fracturing job is completed), themodeling application 146 can proceed to block 846. At block 846, themodeling application 146 can report out the data (e.g., sensor data 828)and results of the completed pumping sequence and associated fracturingjob. Also, at block 846, the managing application 136 can place thefracturing fleet in an off or standby state.

A method for modifying a pumping sequence in real time during a pumpingoperation based on monitored well sites to achieve the desired fracturepropagation is described. The sensor data from a monitored wellsite(e.g., wellsite 138 & 140 from FIG. 2A) may indicate that the formationis fracturing in a different manner than modeled. A modified fracturemodel can be generated on the fly (e.g., while the fracturing job isongoing) using the real time sensor data from the treated wellsiteand/or the monitored well sites. Turning now to FIG. 10, a method 850for modifying a pumping sequence in real time is described as a logicalflow diagram. At block 852, the pumping sequence can be loaded into themodeling application 146 executing on the computer 142 within thecontrol van 110. The associated automated pumping sequence (e.g., theautomated pumping sequence corresponding to the pumping sequenceuploaded to the modeling application 146) can be loaded into themanaging application 136 on the computer 132 within the control van 110.In an aspect, modeling application 146 and managing application 136 canbe executing on the same computer or server.

At block 854, the modeling application 146 receives sensor data 856,which may include (A) sensor data 174 from the treated wellbore, whichmay further include (i) sensor data from the wellsite monitoring system50 in FIG. 1 that includes subsurface data collected from the wellboreand/or surrounding formation; (ii) surface data that may be collectedfrom the fracturing spread of FIG. 2A via unit sensors module 152, asshown in FIG. 3); or (iii) both (i) and (ii); (B) sensor data 172 and/orsensor data 176 from one or more remote, monitoring well sites 138and/or 140, respectively, as shown in FIG. 2A, which may further includesubsurface sensor data collected from with a wellsite monitoring system50 of the type described with reference to FIG. 1 installed at wellsite138 and/or 140 in FIG. 2A; or (C) both (A) and (B). The modelingapplication 146 can use the sensor data 856 to determine a current orreal time state of the model, which may correspond to a current or realtime parameter of the pumping sequence (e.g., pressure, flow rate,proppant amount frac fluid composition, etc.), a current or real timeparameter of the fractures in the formation (e.g., size, number,geometry, etc. of fractures), or combinations thereof. At block 858, themodeling application 146 may further compare the current or real timestate of the model (and correspondingly one or more current or real timeparameters of the pumping sequence and/or formation fracture profile) toan expected or predicted state of the model to identify any differencesbetween expected/predicted/target values of parameters and current/realtime values of parameters associated with the pumping sequence and/orformation fracture profile.

If one or more of the current or real time parameters of the fracturingjob derived from sensor data 828 does not deviate from the correspondingtarget/predicted parameters by more than a predefined delta, the methodproceeds to block 859 to determine if the fracturing job is completed.If the frac job is completed, the method proceeds to finish. If the fracjob is not completed, the method returns to block 854 to continueiteratively checking the current, real time status of the fracturing jobto the modeled, predicted status of the fracturing job. Upon returningto block 854, the modeling application 146 receives updated sensor data856 (e.g., data that has been updated to correspond with a periodicpassage of time) and the method proceeds iteratively as described withreference to blocks 854, 858, and 859.

If one or more of the current or real time parameters of the fracturingjob derived from sensor data 828 deviate from the correspondingtarget/predicted parameters by more than a predefined delta, theautomated sub-stage routine 848 proceeds to block 862 to run anautomated sub-stage routine 860. The automated sub-stage routine 860 canbe a script of instructions (e.g., commands) to change the operation ofthe pumping stage in response to an update or modification of thefracture model. The automated sub-stage routine 860 can begin at block862 to generate a modified fracture model using sensor data 856. Themodified fracture model can be iterated any number of times to convergewithin a predefined value based upon the sensor data 856. In an aspect,the modified model produced by the modeling application 146 at block 862is performed in accordance with the fracture modeling at block 804 ofFIG. 8.

The modeling application 146 can step to block 864 to determine if themodified fracture model is optimized per the inputted target values. Inan aspect, the optimized model produced by the modeling application 146at block 864 is performed in accordance with the model optimization atblock 808 of FIG. 8.

If the modified fracture model is not optimized at block 864, the methodcan proceed to block 866, where one or more targets or inputs of a givenfracturing job (e.g., a stage of a fracturing job) may be modified(e.g., automatically and/or via user input) and thereby provide acorresponding one or more modified targets (e.g., modified stagetargets). If the modified stage targets are within a predefined range(e.g., within the acceptable ranges of corresponding values used by theinitial model to develop the initial pumping sequence), the methodproceeds to block 862 with the modified stage targets. At block 862, theautomated sub-stage routine 860 determines the modified fracture modelusing the modified targets. If at block 866, the modified stage targetsare outside a predefined range, the exception script will proceed toblock 868 to notify the user (e.g., service personnel) of an exception.At block 868, the automated sub-stage routine 860 notifies the users ofan exception and returns control or partial control to the user. Theuser can perform any or all of the mitigating steps including manuallysetting one or more new or modified stage targets, terminating theautomated sub-stage routine 860, ending the active pumping stage, ormanually controlling the frac fleet. The automated stage routine canproceed iteratively as described with reference to blocks 862, 864, 866,and 868 until the modified model is optimized.

At block 864, if the modified fracture model has been optimized, thenthe method proceeds to block 870 and the iterative execution of theautomated sub-stage routine 860 ends. At block 870, the modelingapplication 146 generates a modified pumping sequence using the modifiedfracture model. The modeling application 146 sends the modified pumpingsequence to the managing application 136. At block 872, the managingapplication 136 can generate a modified automated pumping sequence(e.g., comprising a plurality of pumping sub-stage scripts) and use themodified automated pumping sequence to update and continue thefracturing job in real time. The fracture modeling routine/method 850restarts at block 852 with the modified pumping sequence and modifiedautomated pumping sequence generated at blocks 870 and 872,respectively.

In an embodiment, the fracture modeling routine/method 850 can usemodeling application 146 executing on the computer 142 within thecontrol van 110 to produce a pumping sequence (e.g., an initial pumpingsequence loaded at block 852 and/or a modified pumping sequence preparedat block 870) as disclosed herein, for example with reference to FIG.10. The managing application 136 executing on computer 132 within thecontrol van 110 can receive the pumping sequence from the modelingapplication 146 to produce the automated pumping sequence (e.g., aninitial automated pumping sequence loaded at block 852 and/or a modifiedautomated pumping sequence prepared at block 872).

In an embodiment, the fracture modeling routine/method 850 can usemodeling application 224 executing on the computer 222 within theservice center 220 to produce a pumping sequence (e.g., an initialpumping sequence loaded at block 852 and/or a modified pumping sequenceprepared at block 870) as disclosed herein, for example with referenceto FIG. 10. The managing application 136 executing on computer 132within the control van 110 can receive the pumping sequence from themodeling application 224 or from the storage computer 214 via network212 to produce the automated pumping sequence (e.g., an initialautomated pumping sequence loaded at block 852 and/or a modifiedautomated pumping sequence prepared at block 872).

In an embodiment, the method 800 can use modeling application 224executing on the computer 222 within the service center 220 to produce apumping sequence (e.g., an initial pumping sequence loaded at block 852and/or a modified pumping sequence prepared at block 870) as disclosedherein, for example with reference to FIG. 10. The managing application225 executing on computer 222 within the service center 220 can receivethe pumping sequence from the modeling application 224 to produce theautomated pumping sequence (e.g., an initial automated pumping sequenceloaded at block 852 and/or a modified automated pumping sequenceprepared at block 872), which can be saved in storage computer 214and/or provided via network 212 to managing application 136 executing oncomputer 132 at control van 110.

In an embodiment, the method 800 can use modeling application 146executing on the computer 142 within the control van 110 to produce apumping sequence (e.g., an initial pumping sequence loaded at block 852and/or a modified pumping sequence prepared at block 870) as disclosedherein, for example with reference to FIG. 10. The modeling application146 can send the pumping sequence to storage computer 214 via network212. The managing application 136 executing on computer 132 within thecontrol van 110 can receive the pumping sequence from the modelingapplication 224 or from the storage computer 214 via network 212 toproduce the automated pumping sequence (e.g., an initial automatedpumping sequence loaded at block 852 and/or a modified automated pumpingsequence prepared at block 872).

In an embodiment, the method 800 can use modeling application 146executing on the computer 142 within the control van 110 to produce apumping sequence (e.g., an initial pumping sequence loaded at block 852and/or a modified pumping sequence prepared at block 870) as disclosedherein, for example with reference to FIG. 10. The modeling application146 can send the pumping sequence to storage computer 214 via network212. The managing application 225 executing on computer 222 within theservice center 220 can receive the pumping sequence from the storagecomputer 214 and produce the automated pumping sequence (e.g., aninitial automated pumping sequence loaded at block 852 and/or a modifiedautomated pumping sequence prepared at block 872), which can be saved instorage computer 214 and/or provided via network 212 to managingapplication 136 executing on computer 132 at control van 110.

A method for executing and/or modifying a pumping sequence in real timeduring a pumping operation based on monitored well sites to achieve thedesired fracture propagation is described. The sensor data from amonitored wellsite (e.g., wellsite 138 & 140 from FIG. 2A) gatheredduring a pumping sequence may indicate that the formation is fracturingin a different manner than modeled. A modified or alternative pumpingsequence can be executed based upon the updated model using the sensordata from the treated wellsite and/or the monitored well sites. Turningnow to FIG. 11, a method 900 for executing a pumping sequence isdescribed as a logical flow diagram.

At block 902, a list of performance criteria (and an associated rankingof priority or importance for each member of the list of performancecriteria) for a given fracturing job is loaded into the modelingapplication 146 executing on the computer 142 within the control van110. Additionally, limits for one or more control variables of thefracturing job (e.g., frac unit control variables) may be set and/ormodified (e.g., max and min pressures, flow rates, proppantconcentration, etc.). In an aspect, the listing and ranking of frac jobperformance criteria and/or the setting/modifying of control variablelimits are performed in accordance with the set targets at block 802 ofFIG. 8 (or vice-versa).

At block 904, one or more fracture modeling applications (e.g., one ormore modeling applications 146) can be loaded into computer 142 incontrol van 110 modeling application 146 or otherwise accessed andactivated by computer 142 such that a fracture job may be modeled basedupon the input at block 802 (e.g., target performance criteria andtarget limits). Each fracture modeling application can comprise machinealgorithms for calculating pumping flowrate, pumping pressure, andproppant density based on the input at block 802 (and/or an input ofwellbore sensor data as described herein). The fracture modelingapplication can provide a pumping sequence 300 of the type shown inFIGS. 6A and 6B. In an aspect, the fracture modeling and production of aresultant pumping sequence are performed in accordance with thehierarchy described for fracture modeling control component 164 andpumping sequence control of FIG. 4 and/or model fracture at block 804and pumping sequence at block 806 of FIG. 8 (or vice-versa).

At block 906, the modeling application 146 can monitor the equipmentdata and the wellbore sensor data as the fracturing job starts andprogresses (e.g., monitor that status of an automated pumping sequenceexecuting on the managing application 136 as described herein, forexample, with reference to pumping sequence control component 166 ofFIG. 4). The modeling application 146 can monitor the progress of anongoing fracturing job, for example, by periodically comparing theequipment data and sensor data (e.g., wellbore sensor data 172, 174, &176 from FIG. 4) to predetermined setpoints or targets for variousperformance criteria and/or control variables associated with thefracturing job, for example with reference to block 854 of FIG. 10. Thesensor data may include (A) sensor data 174 from the treated wellbore,which may further include (i) sensor data from the wellsite monitoringsystem 50 in FIG. 1 that includes subsurface data collected from thewellbore and/or surrounding formation; (ii) surface data that may becollected from the fracturing spread of FIG. 2A via unit sensors module152, as shown in FIG. 3); or (iii) both (i) and (ii); (B) sensor data172 and/or sensor data 176 from one or more remote, monitoring wellsites 138 and/or 140, respectively, as shown in FIG. 2A, which mayfurther include subsurface sensor data collected from with a wellsitemonitoring system 50 of the type described with reference to FIG. 1installed at wellsite 138 and/or 140 in FIG. 2A; or (C) both (A) and(B). In comparing the progress of the present fracturing job (asdetermined using the sensor data) to the associated progress predictedby the model, the modeling application 146 may employ one or moresub-models (and/or the modeling application 146 may be comprised of aplurality of fracture modeling modules), for example as shown at blocks910A-Z. The process flow includes a number of sub-models at block910A-Z, and these sub-models may be more relevant at different timesduring the frac stage treatment/execution. Some sub-models are used atthe beginning of the treatment to achieve specific objects, and othersare targeting the middle or end of the treatment schedule.

The modeling application 146 can step to one of the blocks 910A-Z to runa pumping routine model depending on the pumping stage and/or sensordata. Each pumping routine model can include a closed loop algorithm.The algorithm can calculate the pumping equipment settings (flow rate,pressure, etc.) based on proprietary mathematical formulas and sensordata. The algorithm can be closed loop so that the pumping routine modelcontinues to execute until the end of the pumping stage or a change inthe sensor data. Various control algorithms/models at blocks 910A-Z maybe used to model/calculate treatment schedules/frac spread targetparameters to achieve certain outcomes. The various models at blocks910A-Z may be used individually in a closed loop control mode where thesystem switch between selected models in a predetermined sequence or incombinations of predictive models/modes where the system seeks tooptimize the frac treatment outcome based on various criteria, either ina closed loop or open loop mode or a combination of closed loop/openloop mode. Some of the models may predominantly be used in, e.g., thefirst 1/10, ¼, ⅓, or ½ of the treatment (ProdigiAB at block 910A,Proppant Ramp at block 910B, Cluster Efficiency at block 910C), whereasothers may predominantly be used in the middle ⅘, ½, or ⅓ of thetreatment sequence (Diversion at block 910D, Complexity at block 910E)whereas yet others may mainly be used in the last 1/10, ¼, ⅓, or ½ ofthe treatment schedule (Well Interaction at block 910G) and thetransition between the algorithms may be done after a step where thecurrent treatment progress is evaluated against various pre-determinedcriteria (e.g., at block 906, for example as described with reference toblock 854 of FIG. 10). Some algorithms may be used for a longer durationin a pre-determined sequence like, e.g., ProdigiAB at block 910A—ACM atblock 910F—Well Interaction at block 910G, where ACM may be used 70-95%of the stage treatment.

The performance criteria (e.g., customer objectives) for evaluating thefracturing job may be one or more of: optimize fracturing of unproducedreservoir volume; minimize misplaced proppant; keep fracture overlapbetween target volumes within certain boundaries; optimize outcomes ofproduction models based on predicted fracturelengths/widths/heights/contacted reservoir volumes and production rates;achieve financial targets based on the given cost of BOE/cost oftreatment/predicted or modeled production; minimize negative wellinteraction effects within given boundaries; optimize clusterefficiency; maintain treating pressures and proppant/diverter volumeswithin given/modeled ranges; any other physics based model or datadriven model or combinations of physics based/data driven models, or anycombination thereof. A set of target criteria and rules may be developedbased on customer objectives and these target criteria be developedjointly with the customer or may be based on data driven approachesgiven that an oilfield service company may pump a large number of fracjobs and may use data from a number of these jobs to develop targetcriteria/rules/automated treatment schedules. The data driven approachesmay use any of the selected treatment data, sensor data, engineeredvalues calculates based on treatment and/or measured sensor data, and/ordata from drilling/logging while drilling, and/or surveys/logging runs,and/or data production and well data publicly available, and/or measuredproduction data from individual wells. The data driven approaches may belimited by customer objectives on a field level, pad level, well leveland/or individual stage level. Control variables may include one or moreof pressure, flow rate, proppant concentration, proppant size/type,chemicals (friction reducers, gelling agents, etc.), volumes, liquidtype, the density of pumped fluids, etc. Target variables may includeone or more of pressure in treatment well, pressure in monitoring well,flow rate per cluster, misplaced proppant, misplaced volume, fracturelengths/heights/widths, maximum or minimum values of any targetvariable, growth rates of any target variables or any calculated valuesas a function of one or more target and/or control variables. Valuesand/or limits for these performance criteria can be input and/or updatedas described in accordance with block 802 of FIG. 8 and block 902 ofFIG. 11 (and vice-versa).

At block 910A, the modeling application 146 can execute a pumpingroutine model for pumping frac fluid in a manner to open (e.g., fill theperforation) with proppant. The pumping routine model may be a closedloop algorithm to establish or modify a pumping sequence with fluidflowrate, proppant density, and pump pressure for uniform fluidallocation among perforations or perforation clusters. In an aspect, onesuch pumping routine model is ProdigiAB from Halliburton.

At block 910B, the modeling application 146 can execute a pumpingroutine model for increasing the proppant concentration at a controlledrate based on sensor feedback. The rate of increasing the proppantconcentration must be controlled to prevent screen-out where a largeconcentration of proppant causes a plugging of the perforations. Theclosed loop algorithm will increase the concentration to maximize theamount of proppant pumped into the formation. In an aspect, one suchpumping routine model is Proppant Ramp from Halliburton.

At block 910C, the modeling application 146 can execute a pumpingroutine model to optimize the placement of proppant into theperforations. The pumping routine model can determine the ratio orpercentage of perforations receiving proppant based on sensor data fromthe treatment well and frac units. The pumping routine model can modifythe targets of the pumping sequence or determine a new pumping sequencefor the modeling application 134. The algorithm may include misplacedproppant calculations where misplaced proppant is defined as the amountof cumulative proppant pumped through overstimulated clusters beyond themean or target proppant allocation, and physics based and/or data drivenmodels to minimize misplaced proppant. In an aspect, one such pumpingroutine model is Cluster Efficiency from Halliburton.

At block 910D, the modeling application 146 can execute a pumpingroutine model to determine if and/or when to drop diversion material tochange the flow distribution of proppant into a set of perforations. Thepumping routine model can include a closed loop control algorithm tomeasure subsurface properties and calculate if/when to drop particulatematerial with the objective of changing flow distribution betweenperforations/perforation clusters. The algorithm may include changes ofsurface flow rate combined while adding diverter material at surface tominimize diverter material dispersion/maximize concentration, ramping upflow rate to move the diverter pill to the subsurface, and also reducethe flow rate when the diverter pill hits the perforations for properseating/distribution. In an aspect, one such pumping routine model isDiversion from Halliburton.

At block 910E, the modeling application 146 can execute a pumpingroutine model to determine if a change to the pumping sequence is neededbased on the sensor data. The pumping routine model can include a closedloop control algorithm to measure subsurface properties and modelcomplexity based on various treatment scenarios. The algorithm mayinclude data driven models for fracture properties based on changes inpressure, rates, diversion, proppant concentrations and rate of changesof said parameters. In an aspect, one such pumping routine model isComplexity from Halliburton.

At block 910F, the modeling application 146 can execute a pumpingroutine model to combine diverter drops with changes in pumping rates toachieve a target. The pumping routine model can include a closed loopcontrol algorithm to measure sensor data, model various reservoirproperties and control targets/treatment schedule to the automated fracfleet (e.g., managing application) to achieve a combination of diverterdrops/rates/pressures within the modeled targets per algorithm. Thealgorithm calculates a pressure fairway and the target treatmentschedule works within an upper/lower bound of pressure as diverterconcentration, proppant concentration and/or chemical concentration isvaried. In an aspect, one such pumping routine model is ACM fromHalliburton.

At block 910G, the modeling application 146 can execute a pumpingroutine model to measure and monitor reservoir communication between atreatment well and a monitored wellsite, and modify a pumping sequenceaccordingly. The pumping routine model can include a closed loop controlalgorithm that measures well interaction related properties and modeldifferent scenarios where well interference effects can be controlled. Anumber of measurements can be used to model well interaction effects:Monitor well pressure changes may indicate pressure communicationthrough reservoir deformation as fractures approach the well where thesignature and/or magnitude of the pressure measurement can be used tomodel well interaction effects and various control actions can bemodeled to change the outcome of these well interaction events.Similarly, Distributed Acoustic Sensing (DAS) based MicroSeismicMonitoring (MSM) may be used to measure microseismic events and thisdata can be used to map/model fracture length/width/height/azimuth andassociated growth rates as well as predict final fracture lengths.Distributed Strain Sensing (DSS) can be used to measure strain changesalong the wellbore during the fracture operation, and the strain can beused to model the associated fractures/volumes that would be required togenerate a similar distributed strain profile. The fracturegeometry/volumes as well as associated growth rates can be used topredict the outcome of the fracturing treatment and associated willinterference effects. A number of different sub-algorithms can be usedto measure/model well interaction effects and make predictions based onvarious control actions/control variables/target variables.

At block 912, the modeling application 146 can optionally visualizeand/or aggregate the sensor data, modeled data/parameters, and equipmentand sensor status associated with the present fracturing job. Suchvisualization can be output to a user, for example via a report, alert,or user interface.

At block 914, the modeling application 146 may further compare thecurrent or real time state of the model or combination of sub-models atblock 910A-Z (and correspondingly one or more current or real timeparameters of the pumping sequence and/or formation fracture profile) toan expected or predicted state of the model or sub-models at block910A-Z to identify any differences between expected/predicted/targetvalues of parameters and current/real time values of parametersassociated with the pumping sequence and/or formation fracture profile.That is, the modeling application 146 can determine if the pumpingsequence needs to be modified by the delta between the sensor data andthe updated model. If so, the modeling application 146 can update thethe pumping sequence to provide a modified pumping sequence (e.g., toalter the fracture propagation within the formation in real time) basedon the updated modeling (e.g., re-modeling). If not, the modelingapplication 146 can leave the pumping sequence as is (e.g., unmodifiedpumping sequence). In an aspect, the updating and/or optimization of themodel at blocks 906, 910, 912, 914, and 916 can be carried out inaccordance with fracture modeling routine/method 850 of FIG. 10.

At block 916, the modeling application 146 can communicate the pumpingsequence (e.g., a modified or unmodified pumping sequence) to the userand send the pumping sequence to the managing application (e.g.,managing application 136). The managing application can modify theautomated pumping sequence with the modified pumping sequence andfurther proceed with carrying out the fracturing job, for example inaccordance with method 820 as shown in FIG. 9.

At block 918, the modeling application 146 can communicate selected datato the user (e.g., service personnel) and/or save the data set to aserver (e.g., storage computer 214). The selected data set can be thedata set that prompted the execution of a pumping sequence models.

At block 920, the modeling application 146 can determine if a model setpoint or target needs was modified. If the pumping sequence (e.g., amodified pumping sequence) changed one or more set points or targets,the modeling application returns to block 902 where the modified setpoint or target can be compared to any applicable corresponding limits(e.g., max or min values). If the pumping sequence did not require anychanges to set points or targets, the modeling application proceeds toblock 922.

At block 922, the modeling application 146 checks the operational statusof the current stage. If the stage is not competed, the modelingapplication 146 proceeds to block 906 and the pumping stage continues.If the pumping stage is completed, the modeling application 146 proceedsto block 924.

At block 924, the modeling application 146 can perform end of stageactivities including writing data to a server (e.g., storage computer214) and/or sending a report to a user. At block 926, the modelingapplication checks the operational status of the fracturing job. Themodeling application 146 returns to block 902, if the last stagecompleted is not the last stage of the pumping sequence (i.e., if thejob is not complete). If the job is complete, the method proceeds toblock 928 and the modeling application 146 can perform end of jobactivities including writing data to a server (e.g., storage computer214) and/or sending a report to a user.

An automated pumping sequence 350 may follow the same logical stepsthrough each pump sub-stage (e.g., 320) while fracturing multiplewellbores (e.g., separate and distinct wells, separate wellbores (e.g.,lateral wellbores) sharing a common vertical portion or wellhead, orcombinations thereof). In an embodiment, a control van 110 of FIG. 2Acan be connected to a first set of frac units (e.g., a first frac fleet)and a second set of second frac units (e.g., a second frac fleet). Thefirst frac fleet can be connected to a first treatment well 130 for ahydraulic fracturing treatment. The second frac fleet can be connectedto a second treatment well for a hydraulic fracturing treatment. Theautomated pumping sequence 350 can direct a simultaneous fracturetreatment of the first and second treatment well (e.g., 130) or thesequential treatment of the first and second well. In an aspect, thefirst and second treatment wells can be treated in a combination ofsimultaneous or sequential fracturing stages where the fracturing fluidcan be pumped into the first and second treatment wells simultaneouslyin some stages or sub-stages, sequentially in some stage or sub-stages,or combinations thereof in accordance with a pumping sequence associatedwith the fracturing job.

In an embodiment, the managing application 136 can determine thesequence of pump stages with stage targets from the automated pumpingsequence 350 for a sequential treatment. The managing application 136(e.g., pumping sequence control 166 from FIG. 4) can establishsupervisory control 168 and unit control 170A-Z on a first frac fleetand on a second frac fleet. The automated pumping sequence 350 candirect the first frac fleet to treat (e.g., pump frac fluid) a firstzone in the first treatment well 130, then direct the second frac fleetto treat (e.g., pump frac fluid) a first zone in the second treatmentwell. The managing application 136 can receive sensor data 174 from thefirst treatment well 130 and second treatment well during the treatmentof the first treatment well. The managing application 136 can receivesensor data 174 from the first treatment well 130 and second treatmentwell during the treatment of the second treatment well. The managingapplication 136 can modify one or more of the sub processes (e.g.,closed loop pump sequences for the first well, the second well, or both)based on the sensor data received from one or more wellbores.

In an embodiment, the managing application 136 can determine thesequence of pump stages with stage targets from the automated pumpingsequence 350 for a simultaneous treatment. The managing application 136(e.g., pumping sequence control 166 from FIG. 4) can establishsupervisory control 168 and unit control 170A-Z on a first frac fleetand on a second frac fleet. The automated pumping sequence 350 candirect the first frac fleet to treat (e.g., pump frac fluid) a firstzone in the first treatment well 130 while simultaneously, or nearsimultaneously, directing the second frac fleet to treat (e.g., pumpfrac fluid) a first zone in the second treatment well. The managingapplication 136 can receive sensor data 174 from the first treatmentwell 130 and second treatment well during the near simultaneoustreatment of the first treatment well 130 and second treatment well. Themanaging application 136 can modify one or more of the sub processes(e.g., closed loop pump sequences for the first well, second well, orboth) based on the sensor data received from one or more wells.

Turning now to FIG. 12, a method 230 is described. In an embodiment, themethod 230 is a method of controlling a pumping sequence of a fracturingfleet at a wellsite while performing a fracturing job on a treatmentwellbore penetrating a subterranean formation. At block 232, the method230 comprises receiving during the fracturing job, by a modelingapplication executing on a computer, one or more wellbore inputscomprising sensor data from the treatment wellbore and sensor data fromone or more monitoring wellbores spaced a distance apart from thetreatment wellbore.

At block 234, the method 230 comprises predicting, by the modelingapplication, a fracture propagation within the subterranean formationusing all or a portion of the inputs.

At block 236, the method 230 comprises producing during the fracturingjob, by the modeling application, an updated pumping sequence to obtainthe fracture propagation.

At block 238, the method 230 comprises controlling, by a managingapplication, the fracturing fleet in accordance with the updated pumpingsequence to place a fracturing fluid in the treatment well.

Turning now to FIG. 13, a method 250 is described. In an embodiment, themethod 250 is a method of controlling a pumping sequence of a fracturingfleet at a wellsite while performing a fracturing job on a treatmentwellbore penetrating a subterranean formation.

At block 252, the method 250 comprises receiving, by a modelingapplication executing on a computer, one or more user inputs related tothe fracturing job, one or more equipment inputs comprising sensor datafrom one or more frac units of the fracturing fleet, one or morewellbore inputs comprising sensor data from the wellbore, orcombinations thereof.

At block 254, the method 250 comprises predicting, by the modelingapplication, a fracture propagation within the subterranean formationusing all or a portion of the inputs.

At block 256, the method 250 comprises producing, by the modelingapplication, a pumping sequence to obtain the fracture propagation,wherein the pumping sequence comprises two or more sub-stages, andwherein the modeling application employs a first pumping routine modelto provide a first sub-stage of the pumping sequence and employs asecond pumping routine model to provide a second sub-stage of thepumping sequence, wherein the first and second pumping routine modelsare different.

At block 258, the method 250 comprises controlling, by a managingapplication, the fracturing fleet in accordance with the pumpingsequence to place a fracturing fluid in the treatment well.

Turning now to FIG. 14A, an exemplary communication system 550 isdescribed suitable for implementing one or more embodiments disclosedherein, for example implementing communications or messaging asdisclosed herein including without limitation any aspect of wirelesscommunication 46 on FIG. 1; communications with the wellsite of FIG. 2A(e.g., control van 110 and associated computing systems); any aspect ofcommunications with a unit level control system as shown in FIG. 3(e.g., control module 150, sensors 152); any aspect of communicationswith the computing components and network associated with FIG. 5 (e.g.,data communication system 200); etc. Typically, the communication system550 includes a number of access nodes 554 that are configured to providecoverage in which UEs 552 such as cell phones, tablet computers,machine-type-communication devices, tracking devices, embedded wirelessmodules, and/or other wirelessly equipped communication devices (whetheror not user operated), can operate. The access nodes 554 may be said toestablish an access network 556. The access network 556 may be referredto as a radio access network (RAN) in some contexts. In a 5G technologygeneration an access node 554 may be referred to as a gigabit Node B(gNB). In 4G technology (e.g., long term evolution (LTE) technology) anaccess node 554 may be referred to as an enhanced Node B (eNB). In 3Gtechnology (.e.g., code division multiple access (CDMA) and globalsystem for mobile communication (GSM)) an access node 554 may bereferred to as a base transceiver station (BTS) combined with a basicstation controller (BSC). In some contexts, the access node 554 may bereferred to as a cell site or a cell tower. In some implementations, apicocell may provide some of the functionality of an access node 554,albeit with a constrained coverage area. Each of these differentembodiments of an access node 554 may be considered to provide roughlysimilar functions in the different technology generations.

In an embodiment, the access network 556 comprises a first access node554 a, a second access node 554 b, and a third access node 554 c. It isunderstood that the access network 556 may include any number of accessnodes 554. Further, each access node 554 could be coupled with a corenetwork 558 that provides connectivity with various application servers559 and/or a network 560. In an embodiment, at least some of theapplication servers 559 may be located close to the network edge (e.g.,geographically close to the UE 552 and the end user) to deliverso-called “edge computing.” The network 560 may be one or more privatenetworks, one or more public networks, or a combination thereof. Thenetwork 560 may comprise the public switched telephone network (PSTN).The network 560 may comprise the Internet. With this arrangement, a UE552 within coverage of the access network 556 could engage inair-interface communication with an access node 554 and could therebycommunicate via the access node 554 with various application servers andother entities.

The communication system 550 could operate in accordance with aparticular radio access technology (RAT), with communications from anaccess node 554 to UEs 552 defining a downlink or forward link andcommunications from the UEs 552 to the access node 554 defining anuplink or reverse link. Over the years, the industry has developedvarious generations of RATs, in a continuous effort to increaseavailable data rate and quality of service for end users. Thesegenerations have ranged from “1G,” which used simple analog frequencymodulation to facilitate basic voice-call service, to “4G”—such as LongTerm Evolution (LTE), which now facilitates mobile broadband serviceusing technologies such as orthogonal frequency division multiplexing(OFDM) and multiple input multiple output (MIMO).

Recently, the industry has been exploring developments in “5G” andparticularly “5G NR” (5G New Radio), which may use a scalable OFDM airinterface, advanced channel coding, massive MIMO, beamforming, mobilemmWave (e.g., frequency bands above 24 GHz), and/or other features, tosupport higher data rates and countless applications, such asmission-critical services, enhanced mobile broadband, and massiveInternet of Things (IoT). 5G is hoped to provide virtually unlimitedbandwidth on demand, for example providing access on demand to as muchas 20 gigabits per second (Gbps) downlink data throughput and as much as10 Gbps uplink data throughput. Due to the increased bandwidthassociated with 5G, it is expected that the new networks will serve, inaddition to conventional cell phones, general internet service providersfor laptops and desktop computers, competing with existing ISPs such ascable internet, and also will make possible new applications in internetof things (IoT) and machine to machine areas.

In accordance with the RAT, each access node 554 could provide serviceon one or more radio-frequency (RF) carriers, each of which could befrequency division duplex (FDD), with separate frequency channels fordownlink and uplink communication, or time division duplex (TDD), with asingle frequency channel multiplexed over time between downlink anduplink use. Each such frequency channel could be defined as a specificrange of frequency (e.g., in radio-frequency (RF) spectrum) having abandwidth and a center frequency and thus extending from a low-endfrequency to a high-end frequency. Further, on the downlink and uplinkchannels, the coverage of each access node 554 could define an airinterface configured in a specific manner to define physical resourcesfor carrying information wirelessly between the access node 554 and UEs552.

Without limitation, for instance, the air interface could be dividedover time into frames, subframes, and symbol time segments, and overfrequency into subcarriers that could be modulated to carry data. Theexample air interface could thus define an array of time-frequencyresource elements each being at a respective symbol time segment andsubcarrier, and the subcarrier of each resource element could bemodulated to carry data. Further, in each subframe or other transmissiontime interval (TTI), the resource elements on the downlink and uplinkcould be grouped to define physical resource blocks (PRBs) that theaccess node could allocate as needed to carry data between the accessnode and served UEs 552.

In addition, certain resource elements on the example air interfacecould be reserved for special purposes. For instance, on the downlink,certain resource elements could be reserved to carry synchronizationsignals that UEs 552 could detect as an indication of the presence ofcoverage and to establish frame timing, other resource elements could bereserved to carry a reference signal that UEs 552 could measure in orderto determine coverage strength, and still other resource elements couldbe reserved to carry other control signaling such as PRB-schedulingdirectives and acknowledgement messaging from the access node 554 toserved UEs 552. And on the uplink, certain resource elements could bereserved to carry random access signaling from UEs 552 to the accessnode 554, and other resource elements could be reserved to carry othercontrol signaling such as PRB-scheduling requests and acknowledgementsignaling from UEs 552 to the access node 554

The access node 554, in some instances, may be split functionally into aradio unit (RU), a distributed unit (DU), and a central unit (CU) whereeach of the RU, DU, and CU have distinctive roles to play in the accessnetwork 556. The RU provides radio functions. The DU provides L1 and L2real-time scheduling functions; and the CU provides higher L2 and L3non-real time scheduling. This split supports flexibility in deployingthe DU and CU. The CU may be hosted in a regional cloud data center. TheDU may be co-located with the RU, or the DU may be hosted in an edgecloud data center.

Turning now to FIG. 14B, further details of the core network 558 aredescribed. In an embodiment, the core network 558 is a 5G core network.5G core network technology is based on a service based architectureparadigm. Rather than constructing the 5G core network as a series ofspecial purpose communication nodes (e.g., an HSS node, a MME node,etc.) running on dedicated server computers, the 5G core network isprovided as a set of services or network functions. These services ornetwork functions can be executed on virtual servers in a cloudcomputing environment which supports dynamic scaling and avoidance oflong-term capital expenditures (fees for use may substitute for capitalexpenditures). These network functions can include, for example, a userplane function (UPF) 579, an authentication server function (AUSF) 575,an access and mobility management function (AMF) 576, a sessionmanagement function (SMF) 577, a network exposure function (NEF) 570, anetwork repository function (NRF) 571, a policy control function (PCF)572, a unified data management (UDM) 573, a network slice selectionfunction (NSSF) 574, and other network functions. The network functionsmay be referred to as virtual network functions (VNFs) in some contexts.

Network functions may be formed by a combination of small pieces ofsoftware called microservices. Some microservices can be re-used incomposing different network functions, thereby leveraging the utility ofsuch microservices. Network functions may offer services to othernetwork functions by extending application programming interfaces (APIs)to those other network functions that call their services via the APIs.The 5G core network 558 may be segregated into a user plane 580 and acontrol plane 582, thereby promoting independent scalability, evolution,and flexible deployment.

The UPF 579 delivers packet processing and links the UE 552, via theaccess node 556, to a data network 590 (e.g., the network 560illustrated in FIG. 6A). The AMF 576 handles registration and connectionmanagement of non-access stratum (NAS) signaling with the UE 552. Saidin other words, the AMF 576 manages UE registration and mobility issues.The AMF 576 manages reachability of the UEs 552 as well as varioussecurity issues. The SMF 577 handles session management issues.Specifically, the SMF 577 creates, updates, and removes (destroys)protocol data unit (PDU) sessions and manages the session context withinthe UPF 579. The SMF 577 decouples other control plane functions fromuser plane functions by performing dynamic host configuration protocol(DHCP) functions and IP address management functions. The AUSF 575facilitates security processes.

The NEF 570 securely exposes the services and capabilities provided bynetwork functions. The NRF 571 supports service registration by networkfunctions and discovery of network functions by other network functions.The PCF 572 supports policy control decisions and flow based chargingcontrol. The UDM 573 manages network user data and can be paired with auser data repository (UDR) that stores user data such as customerprofile information, customer authentication number, and encryption keysfor the information. An application function 592, which may be locatedoutside of the core network 558, exposes the application layer forinteracting with the core network 558. In an embodiment, the applicationfunction 592 may be execute on an application server 559 locatedgeographically proximate to the UE 552 in an “edge computing” deploymentmode. The core network 558 can provide a network slice to a subscriber,for example an enterprise customer, that is composed of a plurality of5G network functions that are configured to provide customizedcommunication service for that subscriber, for example to providecommunication service in accordance with communication policies definedby the customer. The NSSF 574 can help the AMF 576 to select the networkslice instance (NSI) for use with the UE 552.

FIG. 15 illustrates a computer system 380 suitable for implementing oneor more embodiments disclosed herein, for example implementing one ormore computers, servers or the like as disclosed or used herein,including without limitation any aspect of the computing systemassociated with control van 110 (e.g., computers 132 and 142); anyaspect of the computing components and network associated with FIG. 5(e.g., computer 222); any aspect of a unit level control system as shownin FIG. 3 (e.g., control module 150); etc. The computer system 380includes a processor 382 (which may be referred to as a centralprocessor unit or CPU) that is in communication with memory devicesincluding secondary storage 384, read only memory (ROM) 386, randomaccess memory (RAM) 388, input/output (I/O) devices 390, and networkconnectivity devices 392. The processor 382 may be implemented as one ormore CPU chips.

It is understood that by programming and/or loading executableinstructions onto the computer system 380, at least one of the CPU 382,the RAM 388, and the ROM 386 are changed, transforming the computersystem 380 in part into a particular machine or apparatus having thenovel functionality taught by the present disclosure. It is fundamentalto the electrical engineering and software engineering arts thatfunctionality that can be implemented by loading executable softwareinto a computer can be converted to a hardware implementation bywell-known design rules. Decisions between implementing a concept insoftware versus hardware typically hinge on considerations of stabilityof the design and numbers of units to be produced rather than any issuesinvolved in translating from the software domain to the hardware domain.Generally, a design that is still subject to frequent change may bepreferred to be implemented in software, because re-spinning a hardwareimplementation is more expensive than re-spinning a software design.Generally, a design that is stable that will be produced in large volumemay be preferred to be implemented in hardware, for example in anapplication specific integrated circuit (ASIC), because for largeproduction runs the hardware implementation may be less expensive thanthe software implementation. Often a design may be developed and testedin a software form and later transformed, by well-known design rules, toan equivalent hardware implementation in an application specificintegrated circuit that hardwires the instructions of the software. Inthe same manner as a machine controlled by a new ASIC is a particularmachine or apparatus, likewise a computer that has been programmedand/or loaded with executable instructions may be viewed as a particularmachine or apparatus.

Additionally, after the computer system 380 is turned on or booted, theCPU 382 may execute a computer program or application. For example, theCPU 382 may execute software or firmware stored in the ROM 386 or storedin the RAM 388. In some cases, on boot and/or when the application isinitiated, the CPU 382 may copy the application or portions of theapplication from the secondary storage 384 to the RAM 388 or to memoryspace within the CPU 382 itself, and the CPU 382 may then executeinstructions that the application is comprised of. In some cases, theCPU 382 may copy the application or portions of the application frommemory accessed via the network connectivity devices 392 or via the I/Odevices 390 to the RAM 388 or to memory space within the CPU 382, andthe CPU 382 may then execute instructions that the application iscomprised of. During execution, an application may load instructionsinto the CPU 382, for example load some of the instructions of theapplication into a cache of the CPU 382. In some contexts, anapplication that is executed may be said to configure the CPU 382 to dosomething, e.g., to configure the CPU 382 to perform the function orfunctions promoted by the subject application. When the CPU 382 isconfigured in this way by the application, the CPU 382 becomes aspecific purpose computer or a specific purpose machine.

The secondary storage 384 is typically comprised of one or more diskdrives or tape drives and is used for non-volatile storage of data andas an over-flow data storage device if RAM 388 is not large enough tohold all working data. Secondary storage 384 may be used to storeprograms which are loaded into RAM 388 when such programs are selectedfor execution. The ROM 386 is used to store instructions and perhapsdata which are read during program execution. ROM 386 is a non-volatilememory device which typically has a small memory capacity relative tothe larger memory capacity of secondary storage 384. The RAM 388 is usedto store volatile data and perhaps to store instructions. Access to bothROM 386 and RAM 388 is typically faster than to secondary storage 384.The secondary storage 384, the RAM 388, and/or the ROM 386 may bereferred to in some contexts as computer readable storage media and/ornon-transitory computer readable media.

I/O devices 390 may include printers, video monitors, liquid crystaldisplays (LCDs), touch screen displays, keyboards, keypads, switches,dials, mice, track balls, voice recognizers, card readers, paper tapereaders, or other well-known input devices.

The network connectivity devices 392 may take the form of modems, modembanks, Ethernet cards, universal serial bus (USB) interface cards,serial interfaces, token ring cards, fiber distributed data interface(FDDI) cards, wireless local area network (WLAN) cards, radiotransceiver cards, and/or other well-known network devices. The networkconnectivity devices 392 may provide wired communication links and/orwireless communication links (e.g., a first network connectivity device392 may provide a wired communication link and a second networkconnectivity device 392 may provide a wireless communication link).Wired communication links may be provided in accordance with Ethernet(IEEE 802.3), Internet protocol (IP), time division multiplex (TDM),data over cable service interface specification (DOCSIS), wavelengthdivision multiplexing (WDM), and/or the like. In an embodiment, theradio transceiver cards may provide wireless communication links usingprotocols such as code division multiple access (CDMA), global systemfor mobile communications (GSM), long-term evolution (LTE), WiFi (IEEE802.11), Bluetooth, Zigbee, narrowband Internet of things (NB IoT), nearfield communications (NFC), radio frequency identity (RFID). The radiotransceiver cards may promote radio communications using 5G, 5G NewRadio, or 5G LTE radio communication protocols. These networkconnectivity devices 392 may enable the processor 382 to communicatewith the Internet or one or more intranets. With such a networkconnection, it is contemplated that the processor 382 might receiveinformation from the network, or might output information to the networkin the course of performing the above-described method steps. Suchinformation, which is often represented as a sequence of instructions tobe executed using processor 382, may be received from and outputted tothe network, for example, in the form of a computer data signal embodiedin a carrier wave.

Such information, which may include data or instructions to be executedusing processor 382 for example, may be received from and outputted tothe network, for example, in the form of a computer data baseband signalor signal embodied in a carrier wave. The baseband signal or signalembedded in the carrier wave, or other types of signals currently usedor hereafter developed, may be generated according to several methodswell-known to one skilled in the art. The baseband signal and/or signalembedded in the carrier wave may be referred to in some contexts as atransitory signal.

The processor 382 executes instructions, codes, computer programs,scripts which it accesses from hard disk, floppy disk, optical disk(these various disk based systems may all be considered secondarystorage 384), flash drive, ROM 386, RAM 388, or the network connectivitydevices 392. While only one processor 382 is shown, multiple processorsmay be present. Thus, while instructions may be discussed as executed bya processor, the instructions may be executed simultaneously, serially,or otherwise executed by one or multiple processors. Instructions,codes, computer programs, scripts, and/or data that may be accessed fromthe secondary storage 384, for example, hard drives, floppy disks,optical disks, and/or other device, the ROM 386, and/or the RAM 388 maybe referred to in some contexts as non-transitory instructions and/ornon-transitory information.

In an embodiment, the computer system 380 may comprise two or morecomputers in communication with each other that collaborate to perform atask. For example, but not by way of limitation, an application may bepartitioned in such a way as to permit concurrent and/or parallelprocessing of the instructions of the application. Alternatively, thedata processed by the application may be partitioned in such a way as topermit concurrent and/or parallel processing of different portions of adata set by the two or more computers. In an embodiment, virtualizationsoftware may be employed by the computer system 380 to provide thefunctionality of a number of servers that is not directly bound to thenumber of computers in the computer system 380. For example,virtualization software may provide twenty virtual servers on fourphysical computers. In an embodiment, the functionality disclosed abovemay be provided by executing the application and/or applications in acloud computing environment. Cloud computing may comprise providingcomputing services via a network connection using dynamically scalablecomputing resources. Cloud computing may be supported, at least in part,by virtualization software. A cloud computing environment may beestablished by an enterprise and/or may be hired on an as-needed basisfrom a third party provider. Some cloud computing environments maycomprise cloud computing resources owned and operated by the enterpriseas well as cloud computing resources hired and/or leased from a thirdparty provider.

In an embodiment, some or all of the functionality disclosed above maybe provided as a computer program product. The computer program productmay comprise one or more computer readable storage medium havingcomputer usable program code embodied therein to implement thefunctionality disclosed above. The computer program product may comprisedata structures, executable instructions, and other computer usableprogram code. The computer program product may be embodied in removablecomputer storage media and/or non-removable computer storage media. Theremovable computer readable storage medium may comprise, withoutlimitation, a paper tape, a magnetic tape, magnetic disk, an opticaldisk, a solid state memory chip, for example analog magnetic tape,compact disk read only memory (CD-ROM) disks, floppy disks, jump drives,digital cards, multimedia cards, and others. The computer programproduct may be suitable for loading, by the computer system 380, atleast portions of the contents of the computer program product to thesecondary storage 384, to the ROM 386, to the RAM 388, and/or to othernon-volatile memory and volatile memory of the computer system 380. Theprocessor 382 may process the executable instructions and/or datastructures in part by directly accessing the computer program product,for example by reading from a CD-ROM disk inserted into a disk driveperipheral of the computer system 380. Alternatively, the processor 382may process the executable instructions and/or data structures byremotely accessing the computer program product, for example bydownloading the executable instructions and/or data structures from aremote server through the network connectivity devices 392. The computerprogram product may comprise instructions that promote the loadingand/or copying of data, data structures, files, and/or executableinstructions to the secondary storage 384, to the ROM 386, to the RAM388, and/or to other non-volatile memory and volatile memory of thecomputer system 380.

In some contexts, the secondary storage 384, the ROM 386, and the RAM388 may be referred to as a non-transitory computer readable medium or acomputer readable storage media. A dynamic RAM embodiment of the RAM388, likewise, may be referred to as a non-transitory computer readablemedium in that while the dynamic RAM receives electrical power and isoperated in accordance with its design, for example during a period oftime during which the computer system 380 is turned on and operational,the dynamic RAM stores information that is written to it. Similarly, theprocessor 382 may comprise an internal RAM, an internal ROM, a cachememory, and/or other internal non-transitory storage blocks, sections,or components that may be referred to in some contexts as non-transitorycomputer readable media or computer readable storage media.

The following are included as specific and non-limiting enumeratedembodiments of the various concepts disclosed herein.

A first embodiment, which is a method of controlling a pumping sequenceof a fracturing fleet at a wellsite while performing a fracturing job ona treatment wellbore penetrating a subterranean formation, comprising:receiving, by a modeling application executing on a computer, one ormore user inputs related to the fracturing job, one or more equipmentinputs comprising sensor data from one or more frac units of thefracturing fleet, one or more wellbore inputs comprising sensor datafrom the wellbore, or combinations thereof; predicting, by the modelingapplication, a fracture propagation within the subterranean formationusing all or a portion of the inputs; producing, by the modelingapplication, a pumping sequence or an updated pumping sequence to obtainthe fracture propagation, wherein the pumping sequence comprises two ormore sub-stages, and wherein the modeling application employs a firstpumping routine model to provide a first sub-stage of the pumpingsequence and employ a second pumping routine model to provide a secondsub-stage of the pumping sequence, wherein the first and second pumpingroutine models are different; and controlling, by a managingapplication, the fracturing fleet in accordance with the pumpingsequence to place a fracturing fluid in the treatment well.

A second embodiment, which is the method of first embodiment, whereinthe pumping sequence corresponds to a pumping time and wherein the firstsub-stage is completed within a first half, alternatively a first third,alternatively a first quarter, or alternatively a first one tenth of thepumping time.

A third embodiment, which is the method of the first or secondembodiment, wherein the modeling application employs a third pumpingroutine model to provide a last sub-stage of the pumping sequence andwherein the first, second, and third pumping routine models aredifferent.

A fourth embodiment, which is the method of the third embodiment,wherein the last sub-stage is completed within a last half,alternatively a last third, alternatively a last quarter, oralternatively a last one tenth of the pumping time.

A fifth embodiment, which is the method of the third or fourthembodiment, wherein the first sub-stage corresponds to ramping up fromzero a flow rate of the pumping sequence and the last sub-stagecorresponds to a ramping down to zero of the flow rate of the pumpingsequence.

A sixth embodiment, which is the method of any of the first to fifthembodiments, wherein the one or more wellbore inputs comprise sensordata gathered from sensors located in the treatment well during thefracturing job.

A seventh embodiment, which is the method of any of the first to sixthembodiments, wherein the one or more wellbore inputs comprise sensordata gathered from sensors located in one or more monitoring wellboresspaced a distance apart from the treatment wellbore.

An eighth embodiment, which is the method of seventh embodiment, whereinthe treatment wellbore and one or more monitoring wellbores are lateralwellbores sharing a common vertical portion.

A ninth embodiment, which is the method of seventh embodiment, whereinthe treatment wellbore and the one or more monitoring wellbores aredistinct from one another and do not share any common borehole.

A tenth embodiment, which is the method of any of the first to ninthembodiments, wherein the fracturing job comprises at least two treatmentwellbores and the predicting by the modeling application predicts thefracture propagation within an area of the subterranean formationlocated adjacent or between the two treatment wells.

An eleventh embodiment, which is the method of the tenth embodiment,wherein the fracturing fluid is placed simultaneously or sequentiallyinto the at least two treatment wellbores.

A twelfth embodiment, which is a method of controlling a pumpingsequence of a fracturing fleet at a wellsite while performing afracturing job on a treatment wellbore penetrating a subterraneanformation, comprising: receiving during the fracturing job, by amodeling application executing on a computer, one or more wellboreinputs comprising sensor data from the treatment wellbore and sensordata from one or more monitoring wellbores spaced a distance apart fromthe treatment wellbore; predicting, by the modeling application, afracture propagation within the subterranean formation using all or aportion of the inputs; producing during the fracturing job, by themodeling application, an updated pumping sequence to obtain the fracturepropagation; and controlling, by a managing application, the fracturingfleet in accordance with the updated pumping sequence to place afracturing fluid in the treatment well.

A thirteenth embodiment, which is the method of the twelfth embodiment,wherein the updated pumping sequence is the same or different than aninitial pumping sequence used at the beginning of the fracturing job.

A fourteenth embodiment, which is the method of the twelfth orthirteenth embodiment, wherein the pumping sequence comprises two ormore sub-stages, and wherein the modeling application employs a firstpumping routine model to provide a first sub-stage of the pumpingsequence and employ a second pumping routine model to provide a secondsub-stage of the pumping sequence, wherein the first and second pumpingroutine models are different.

A fifteenth embodiment, which is the method of any of the twelfth tofourteenth embodiments, wherein the pumping sequence corresponds to apumping time and wherein the first sub-stage is completed within a firsthalf, alternatively a first third, alternatively a first quarter, oralternatively a first one tenth of the pumping time.

A sixteenth embodiment, which is the method of the fourteenth orfifteenth embodiment, wherein the modeling application employs a thirdpumping routine model to provide a last sub-stage of the pumpingsequence and wherein the first, second, and third pumping routine modelsare different.

A seventeenth embodiment, which is the method of sixteenth embodiment,wherein the last sub-stage is completed within a last half,alternatively a last third, alternatively a last quarter, oralternatively a last one tenth of the pumping time.

An eighteenth embodiment, which is the method of the sixteenth orseventeenth embodiment, wherein the first sub-stage corresponds toramping up from zero a flow rate of the pumping sequence and the lastsub-stage corresponds to a ramping down to zero of the flow rate of thepumping sequence.

A nineteenth embodiment, which is the method of any of the twelfth toeighteenth embodiments, wherein the treatment wellbore and one or moremonitoring wellbores are lateral wellbores sharing a common verticalportion.

A twentieth embodiment, which is the method of any of the twelfth toeighteenth embodiments, wherein the treatment wellbore and the one ormore monitoring wellbores are distinct from one another and do not shareany common borehole.

A twenty-first embodiment, which is the method of any of the twelfth totwentieth embodiments, wherein the fracturing job comprises at least twotreatment wellbores and the predicting by the modeling applicationpredicts the fracture propagation within an area of the subterraneanformation located adjacent or between the two treatment wells.

A twenty-second embodiment, which is the method of the twenty-firstembodiment, wherein the fracturing fluid is placed simultaneously orsequentially into the at least two treatment wellbores.

While several embodiments have been provided in the present disclosure,it should be understood that the disclosed systems and methods may beembodied in many other specific forms without departing from the spiritor scope of the present disclosure. The present examples are to beconsidered as illustrative and not restrictive, and the intention is notto be limited to the details given herein. For example, the variouselements or components may be combined or integrated in another systemor certain features may be omitted or not implemented.

Also, techniques, systems, subsystems, and methods described andillustrated in the various embodiments as discrete or separate may becombined or integrated with other systems, modules, techniques, ormethods without departing from the scope of the present disclosure.Other items shown or discussed as directly coupled or communicating witheach other may be indirectly coupled or communicating through someinterface, device, or intermediate component, whether electrically,mechanically, or otherwise. Other examples of changes, substitutions,and alterations are ascertainable by one skilled in the art and could bemade without departing from the spirit and scope disclosed herein.

What is claimed is:
 1. A method of controlling a pumping sequence of afracturing fleet at a wellsite while performing a fracturing job on atreatment wellbore penetrating a subterranean formation, comprising:receiving, by a modeling application executing on a computer, one ormore user inputs related to the fracturing job, one or more equipmentinputs comprising sensor data from one or more frac units of thefracturing fleet, one or more wellbore inputs comprising sensor datafrom the wellbore, or combinations thereof; predicting, by the modelingapplication, a fracture propagation within the subterranean formationusing all or a portion of the inputs; producing, by the modelingapplication, a pumping sequence to obtain the fracture propagation,wherein the pumping sequence comprises two or more sub-stages, andwherein the modeling application employs a first pumping routine modelto provide a first sub-stage of the pumping sequence and employs asecond pumping routine model to provide a second sub-stage of thepumping sequence, wherein the first and second pumping routine modelsare different; and controlling, by a managing application, thefracturing fleet in accordance with the pumping sequence to place afracturing fluid in the treatment well.
 2. The method of claim 1,wherein the pumping sequence corresponds to a pumping time and whereinthe first sub-stage is completed within a first half, alternatively afirst third, alternatively a first quarter, or alternatively a first onetenth of the pumping time.
 3. The method of claim 2, wherein themodeling application employs a third pumping routine model to provide alast sub-stage of the pumping sequence and wherein the first, second,and third pumping routine models are different.
 4. The method of claim3, wherein the last sub-stage is completed within a last half,alternatively a last third, alternatively a last quarter, oralternatively a last one tenth of the pumping time.
 5. The method ofclaim 4, wherein the first sub-stage corresponds to ramping up from zeroa flow rate of the pumping sequence and the last sub-stage correspondsto a ramping down to zero of the flow rate of the pumping sequence. 6.The method of claim 5, wherein the one or more wellbore inputs comprisesensor data gathered from sensors located in the treatment well duringthe fracturing job.
 7. The method of claim 6, wherein the one or morewellbore inputs comprise sensor data gathered from sensors located inone or more monitoring wellbores spaced a distance apart from thetreatment wellbore.
 8. The method of claim 7, wherein the treatmentwellbore and one or more monitoring wellbores are lateral wellboressharing a common vertical portion.
 9. The method of claim 7, wherein thetreatment wellbore and the one or more monitoring wellbores are distinctfrom one another and do not share any common borehole.
 10. The method ofclaim 1, wherein the fracturing job comprises at least two treatmentwellbores and the predicting by the modeling application predicts thefracture propagation within an area of the subterranean formationlocated adjacent or between the two treatment wells.
 11. A method ofcontrolling a pumping sequence of a fracturing fleet at a wellsite whileperforming a fracturing job on a treatment wellbore penetrating asubterranean formation, comprising: receiving during the fracturing job,by a modeling application executing on a computer, one or more wellboreinputs comprising sensor data from the treatment wellbore and sensordata from one or more monitoring wellbores spaced a distance apart fromthe treatment wellbore; predicting, by the modeling application, afracture propagation within the subterranean formation using all or aportion of the inputs; producing during the fracturing job, by themodeling application, an updated pumping sequence to obtain the fracturepropagation; and controlling, by a managing application, the fracturingfleet in accordance with the updated pumping sequence to place afracturing fluid in the treatment well.
 12. The method of claim 11,wherein the updated pumping sequence is the same or different than aninitial pumping sequence used at the beginning of the fracturing job.13. The method of claim 12, wherein the updated pumping sequencecomprises two or more sub-stages, and wherein the modeling applicationemploys a first pumping routine model to provide a first sub-stage ofthe pumping sequence and employ a second pumping routine model toprovide a second sub-stage of the pumping sequence, wherein the firstand second pumping routine models are different.
 14. The method of claim13, wherein the updated pumping sequence corresponds to a pumping timeand wherein the first sub-stage is completed within a first half,alternatively a first third, alternatively a first quarter, oralternatively a first one tenth of the pumping time.
 15. The method ofclaim 14, wherein the modeling application employs a third pumpingroutine model to provide a last sub-stage of the updated pumpingsequence and wherein the first, second, and third pumping routine modelsare different.
 16. The method of claim 15, wherein the last sub-stage iscompleted within a last half, alternatively a last third, alternativelya last quarter, or alternatively a last one tenth of the pumping time.17. The method of claim 16, wherein the first sub-stage corresponds toramping up from zero a flow rate of the updated pumping sequence and thelast sub-stage corresponds to a ramping down to zero of the flow rate ofthe updated pumping sequence.
 18. The method of claim 11, wherein thetreatment wellbore and one or more monitoring wellbores are lateralwellbores sharing a common vertical portion.
 19. The method of claim 11,wherein the treatment wellbore and the one or more monitoring wellboresare distinct from one another and do not share any common borehole. 20.The method of claim 11, wherein the fracturing job comprises at leasttwo treatment wellbores and the predicting by the modeling applicationpredicts the fracture propagation within an area of the subterraneanformation located adjacent or between the two treatment wells.